1773 Inference Jobs - Page 18

Job Summary Gen AI Technical Product Manager Overview: The GenAI Technical Product Manager having expertise to deal use cases exploration as business analyst, Architect develops and implements GEN AI architecture strategies, best practices, and standards to enhance AI ML model deployment and monitoring efficiency. Develop architecture roadmap and strategy for GenAI Platforms and tech stacks. This role will focus on the technical development, deployment, and optimization of GenAI solutions, ensuring alignment with business strategies and technological advancements. Responsibilities: Develop cutting-edge architectural strategies for Gen AI components and platforms, leveraging advanced techniques such as chunking, Retrieval-Augmented Generation (RAG), Ai agents, and embeddings. Balance build versus buy decisions, ensuring alignment with SaaS models and decision trees, particularly for the PepGenX platform. Emphasize low coupling and cohesive model development. Lead working sessions for Arch Alignment, pattern library development, GEN AI Tools Data Architect alignment, tag new components to reuse (components reuse strategy), patterns of the usecases, reuse components ( save efforts, time money). Lead the implementation of LLM operations, focusing on optimizing model performance, scalability, and efficiency. Design and implement LLM agentic processes to create autonomous AI systems capable of complex decision-making and task execution. Work closely with data scientists and AI professionals to identify and pilot innovative use cases that drive digital transformation. Assess the feasibility of these use cases, aligning them with business objectives, ROI and leveraging advanced AI techniques. Gather inputs from various stakeholders to align technical implementations with current and future requirements. Develop processes and products based on these inputs, incorporating state-of-the-art AI methodologies. Define AI architecture and select suitable technologies, with a focus on integrating RAG systems, embedding models, and advanced LLM frameworks. Decide on optimal deployment models, ensuring seamless integration with existing data management and analytics tools. Audit AI tools and practices, focusing on continuous improvement of LLM ops and agentic processes. Collaborate with security and risk leaders to mitigate risks such as data poisoning and model theft, ensuring ethical AI implementation. Stay updated on AI regulations and map them to best practices in AI architecture and pipeline planning. Develop expertise in ML and deep learning workflow architectures, with a focus on chunking strategies, embedding pipelines, and RAG system implementation. Apply advanced software engineering and DevOps principles, utilizing tools like Git, Kubernetes, and CI/CD for efficient LLM ops. Collaborate across teams to ensure AI platforms meet both business and technical requirements. Spearhead the exploration and application of cutting-edge Large Language Models (LLMs) and Generative AI, including multi-modal capabilities and agentic processes. Oversee MLOps, automating ML pipelines from training to deployment with a focus on RAG and embedding optimization. Engage in sophisticated model development from ideation to deployment, leveraging advanced chunking and RAG techniques. Effectively communicate complex analysis results to business partners and executives. Proactively reduce biases in model predictions, focusing on fair and inclusive AI systems through advanced debiasing techniques in embeddings and LLM training. Design efficient data pipelines to support large language model training and inference, with a focus on optimizing chunking strategies and embedding generation for RAG systems. Proven track record in shipping products and developing state-of-the-art Gen AI product architecture. Experience: 10-15 years of experience with a strong balance of business acumen and technical expertise in AI. 5+ years in building and releasing NLP/AI software, with specific experience in RAG , Agents systems and embedding models. Demonstrated experience in delivering Gen AI products, including Multi-modal LLMs, Foundation models, and agentic AI systems. Deep familiarity with cloud technologies, especially Azure, and experience deploying models for large-scale inference using advanced LLM ops techniques. Proficiency in PyTorch, TensorFlow, Kubernetes, Docker, LlamaIndex, LangChain, LLM, SLM, LAM, and cloud platforms, with a focus on implementing RAG and embedding pipelines. Excellent communication and interpersonal skills, with a strong design capability and ability to articulate complex AI concepts to diverse audiences. Hands-on experience with chunking strategies, RAG implementation, and optimizing embedding models for various AI applications. Qualifications: - Bachelor’s or master’s degree in computer science, Data Science, or a related technical field. - Demonstrated ability to translate complex technical concepts into actionable business strategies. Experience in data-driven decision-making processes. - Strong communication skills, with the ability to collaborate effectively with both technical and non-technical stakeholders. - Proven track record in managing and delivering AI/ML projects, with a focus on GenAI solutions, in large-scale enterprise environments.

Job Description: As a Senior Machine Learning Engineer , you will be responsible for designing, developing, and deploying cutting-edge models for end-to-end content generation , including AI-driven image/video generation, lipsyncing, and multimodal AI systems . You will work on the latest advancements in deep generative modeling to create highly realistic and controllable AI-generated media. Responsibilities: Research & Develop : Design and implement state-of-the-art generative models , including Diffusion Models, 3D VAEs and GANs for AI-powered media synthesis . End-to-End Content Generation : Build and optimize AI pipelines for high-fidelity image/video generation and lipsyncing using diffusion and autoencoder models. Speech & Video Synchronization : Develop advanced lipsyncing and multimodal generation models that integrate speech, video, and facial animation for hyper-realistic AI-driven content. Real-Time AI Systems : Implement and optimize models for real-time content generation and interactive AI applications using efficient model architectures and acceleration techniques . Scaling & Production Deployment : Work closely with software engineers to deploy models efficiently on cloud-based architectures (AWS, GCP, or Azure) . Collaboration & Research : Stay ahead of the latest trends in deep generative models, diffusion models, and transformer-based vision systems to enhance AI-generated content quality. Experimentation & Validation : Design and conduct experiments to evaluate model performance, improve fidelity, realism, and computational efficiency , and refine model architectures. Code Quality & Best Practices : Participate in code reviews, improve model efficiency, and document research findings to enhance team knowledge-sharing and product development . Qualifications: Bachelor's or Master’s degree in Computer Science, Machine Learning, or a related field. 3+ years of experience working with deep generative models , including Diffusion Models, 3D VAEs, GANs and autoregressive models . Strong proficiency in Python and deep learning frameworks such as PyTorch. Expertise in multi-modal AI, text-to-image, and image-to-video generation , audio to lipsync Strong understanding of machine learning principles and statistical methods. Good to have experience in real-time inference optimization, cloud deployment, and distributed training . Strong problem-solving abilities and a research-oriented mindset to stay updated with the latest AI advancements. Familiarity with generative adversarial techniques, reinforcement learning for generative models, and large-scale AI model training . Preferred Qualifications: Experience with transformers and vision-language models (e.g., CLIP, BLIP, GPT-4V). Background in text-to-video generation, lipsync generation and real-time synthetic media applications . Experience in cloud-based AI pipelines (AWS, Google Cloud, or Azure) and model compression techniques (quantization, pruning, distillation) . Contributions to open-source projects or published research in AI-generated content, speech synthesis, or video synthesis .

Job Title: Senior Data Scientist, Marketplace Location: Hyderabad About Us: Storable operates the largest online marketplace for self storage, helping millions of consumers find and reserve storage units across thousands of facilities nationwide. Our two-sided platform connects storage operators with renters, enabling smarter pricing, increased occupancy, and better visibility for operators—while simplifying the search and booking experience for consumers. We're growing fast and committed to using data as a competitive advantage in modernizing this legacy industry. The Role: We're looking for a Senior Data Scientist to join our Marketplace team and help shape the future of self storage through data. In this role, you'll lead high-impact initiatives that drive liquidity, optimize search and matching, and improve monetization across our platform. You'll partner cross-functionally to inform product strategy, develop models that enhance customer experience and operator performance, and bring structure to a traditionally opaque industry. This is an ideal opportunity for a deeply analytical, product-oriented thinker who thrives in a fast-moving environment and is excited to shape the evolution of a digital marketplace in a historically offline space. What You'll Do: Analyze marketplace dynamics across supply and demand, uncovering insights to improve conversion, fill rates, and operator performance. Design and evaluate experiments that test pricing strategies, inventory prioritization, and incentive programs for both consumers and storage operators. Build predictive models for customer acquisition, lead quality scoring, pricing elasticity, and churn forecasting. Partner with Product, Engineering, and Sales to develop tools and dashboards that guide marketplace health and operator decision-making. Support the rollout of new features (e.g., dynamic pricing, lead routing, inventory optimization) with data validation, success metrics, and performance analysis. Develop frameworks to balance occupancy and revenue across regions, seasons, and storage types. What You Bring: 7+ years of experience in data science, ideally with exposure to marketplaces, real estate, local services, or platform ecosystems. Strong statistical background with expertise in experimentation, causal inference, and regression modeling. Proficiency in SQL and Python; experience working with large-scale data sets and modern data stacks (e.g., dbt, Airflow, Snowflake). Proven success influencing product strategy and commercial decisions using data. A practical, iterative approach to modeling—balancing speed with rigor in a real-world environment. Experience collaborating cross-functionally with PMs, engineers, analysts, and business leaders. Comfort navigating noisy or incomplete data, especially in fragmented industries like self storage. Bonus Points For: Experience building pricing, search, or lead quality models in a lead-gen or vertical marketplace business. Understanding of the self storage industry, including occupancy economics, customer behavior, and regional trends. Familiarity with geospatial analysis, customer segmentation, or recommender systems.

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together. We are seeking a skilled and motivated AI/ML Engineer with 3–5 years of experience to join our team. The ideal candidate will have hands-on expertise in building and deploying AI/ML solutions on the Azure platform, with a solid focus on Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) systems, and Azure ML Studio. You will play a key role in designing intelligent systems, deploying scalable models, and integrating advanced AI capabilities into enterprise applications. Primary Responsibilities: AI/ML Development & Deployment: Design, develop, and deploy machine learning models using Azure ML Studio and Azure Machine Learning services Build and fine-tune LLM-based solutions for enterprise use cases Develop and implement RAG pipelines using Azure services and vector databases Deploy and monitor AI/ML models in production environments ensuring scalability and performance Azure Platform Engineering: Leverage Azure services such as Azure Data Lake, Azure Synapse, Azure Blob Storage, and Azure Cognitive Search for data ingestion and processing Integrate AI models with Azure-based data pipelines and APIs Use Azure DevOps for CI/CD of ML workflows and model versioning Data Engineering & Processing: Build and maintain ETL/ELT pipelines for structured and unstructured data using Databricks and Apache Spark Prepare and transform data for training and inference using Python, PySpark and SQL LLM & RAG System Implementation: Implement LLM-based agents and chatbots using frameworks like Langchain Design and optimize RAG architectures for domain-specific knowledge retrieval Work with vector databases (e.g., Azure Cognitive Search, FAISS) for embedding-based search Collaboration & Innovation: Collaborate with data scientists, product managers, and engineers to deliver AI-driven features Stay current with advancements in generative AI, LLMs, and Azure AI services Contribute to the continuous improvement of AI/ML pipelines and best practices Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so 3+ years of hands-on experience in AI/ML engineering with a focus on Azure Proven experience in deploying ML models using Azure ML Studio and Azure Machine Learning Experience working with LLMs, RAG systems, and AI agents Experience with Databricks, Apache Spark, and Azure Data services Knowledge of Azure DevOps and CI/CD for ML workflows Understanding of data governance and security in cloud environments Familiarity with MLOps practices and model monitoring tools Familiarity with vector databases and embedding models Proficiency in Python, SQL, and PySpark Proven solid analytical and problem-solving skills Proven effective communication and collaboration with cross-functional teams Proven ability to translate business requirements into technical solutions At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone–of every race, gender, sexuality, age, location and income–deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes — an enterprise priority reflected in our mission.

Designation: Senior Analyst – Data Science Level: L2 Experience: 3 to 6 years Location: Chennai Job Description: We are seeking a highly skilled and motivated Senior Analyst candidate with 3-6 years of experience in Data Science to join our growing team. Responsibilities: Perform analyses on products to answer open-ended questions and provide strategic recommendations. Design and guide experiments/analysis to measure impact and drive product improvements. Develop and maintain key metrics and reports, enhancing data infrastructure for better analysis. Skills: At least a BA/BS in a quantitative field (ex Math, Stats, Physics, or Computer Science) with 2+ years of relevant experience. Key Skillsets looking for: SQL, Python, BI, Statistics, A/B testing, Data Science, Machine Learning Experience driving impact for a digital product with an iterative development cycle. Understanding of statistical concepts and practical experience applying them (in A|B testing, causal inference, ML, etc.). Experience in data analyses using SQL. Experience in programming/modeling in Python. Demonstration of our core cultural values: clear communication, positive energy, continuous learning, and efficient execution. Job Snapshot Updated Date 02-07-2025 Job ID J_3824 Location Chennai, Tamil Nadu, India Experience 3 - 6 Years Employee Type Permanent

Location: Onsite * Note : The selected candidate is required to relocate to Kovilpatti, Tamil Nadu for the initial three-month project training session . Post training, the candidate will be relocated to one of our onsite locations: Chennai, Hyderabad, or Pune , based on project allocation. Job Description The Senior AI Developer will be responsible for designing, building, training, and deploying advanced artificial intelligence and machine learning models to solve complex business challenges across industries. This role demands a strategic thinker and hands-on practitioner who can work at the intersection of data science, software engineering, and innovation. The candidate will contribute to scalable production-grade AI pipelines and mentor junior AI engineers within the Center of Excellence (CoE). Key responsibilities: · Design, train, and fine-tune deep learning models (NLP, CV, LLMs, GANs) for high-value applications · Architect AI model pipelines and implement scalable inference engines in cloud-native environments · Collaborate with data scientists, engineers, and solution architects to productionize ML prototypes · Evaluate and integrate pre-trained models like GPT-4o, Gemini, Claude, and fine-tune based on domain needs · Optimize algorithms for real-time performance, efficiency, and fairness · Write modular, maintainable code and perform rigorous unit testing and validation · Contribute to AI codebase management, CI/CD, and automated retraining infrastructure · Research emerging AI trends and propose innovative applications aligned with business objectives Technical Skills: · Expert in Python, PyTorch, TensorFlow, Scikit-learn, Hugging Face Transformers · LLM deployment & tuning: OpenAI (GPT), Google Gemini, Claude, Falcon, Mistral · Experience with RESTful APIs, Flask/FastAPI for AI service exposure · Proficient in Azure Machine Learning, Databricks, MLflow, Docker, Kubernetes · Hands-on experience with vector databases, prompt engineering, and retrieval-augmented generation (RAG) · Knowledge of Responsible AI frameworks (bias detection, fairness, explainability) Qualification · Master’s in Artificial Intelligence, Machine Learning, Data Science, or Computer Engineering · Certifications in AI/ML (e.g., Microsoft Azure AI Engineer, Google Professional ML Engineer) preferred · Demonstrated success in building scalable AI applications in production environments · Publications or contributions to open-source AI/ML projects are a plus. Job Type: Full-time Pay: Up to ₹80,000.00 per month Location Type: In-person Ability to commute/relocate: Kovilpatti, Tamil Nadu: Reliably commute or willing to relocate with an employer-provided relocation package (Required) Application Question(s): Expected Salary in Annual (INR)? Experience: AI Developer: 8 years (Required) Work Location: In person

Job Summary/Overview: Join our mission to revolutionize education through data-driven innovation, where expertise will directly shape the future of learning. The organization seeks a visionary Research & Data Lead to oversee data-driven product growth initiatives. In this pivotal role, the incumbent will lead the charge in leveraging complex data to unlock new growth opportunities, optimize user engagement, and drive measurable improvements across the adaptive learning platform. This position will define the data strategy, build groundbreaking data products, and cultivate a culture of experimentation and excellence within the data & research team. Roles & Responsibilities: Statistical Modelling & EDA: Lead the design and implementation of advanced statistical models to deeply understand student learning behaviours, profile skills, and inform personalized product experiences that drive engagement and mastery. Drive comprehensive exploratory data analysis on large-scale educational datasets, translating complex patterns and insights into actionable product strategies and growth opportunities. Architect, build, and validate robust multivariate models (e.g., regression, SEM, HLM, Bayesian methods) to rigorously evaluate the causal efficacy of product interventions and inform data-driven product iteration. Algorithm Development & Deployment: Lead the optimization and innovation of Computerised Adaptive Testing (CAT) algorithms and personalized learning pathways to maximize user engagement, learning efficacy, and retention. Work with Psychometricians and Technology teams, to drive the integration of advanced psychometric frameworks with cutting-edge machine learning methods (e.g., classification, predictive analytics, reinforcement learning) to develop and deploy dynamic, AI-powered content recommendation systems that enhance user satisfaction and drive product growth. Cross-Functional Partnership: Serve as a strategic data partner and trusted advisor to Product, Engineering, Instructional Design, and Marketing teams, proactively embedding data-driven insights and experimentation into product roadmaps, feature prioritization, and growth initiatives. Champion data literacy and a culture of experimentation across the organization, translating complex analyses into compelling narratives and actionable recommendations that drive strategic business decisions and product outcomes. Lead, mentor, and inspire a high-performing team of researchers, fostering a culture of technical excellence, innovation, and continuous improvement through rigorous code reviews, knowledge sharing, and professional development. Research & Thought Leadership: Lead advanced research and simulation studies to continuously benchmark, refine, and innovate adaptive learning algorithms, ensuring the product remains at the forefront of educational technology and delivers superior user value and measurable growth." Actively monitor and integrate emerging trends and technologies in educational measurement, AI, ML, and product growth analytics, translating cutting-edge research into practical applications that drive competitive advantage and future product development. Experience Required: PhD or Master’s degree in Statistics, Mathematics, Data Science, or a closely related quantitative field Minimum 5+ years of progressive experience in data science, with at least 3-4 years in a leadership role driving data-driven product growth initiatives, preferably within EdTech or adaptive learning. Proven track record of leveraging advanced statistical modeling, and data driven analytics to inform product strategy, optimize user experiences, and achieve measurable business outcomes in an EdTech or adaptive learning environment. Extensive hands-on experience in designing, executing, and analyzing A/B tests and controlled experiments to drive product iteration and validate hypotheses. Exceptional ability to translate complex business problems and ambiguous product challenges into solvable data science initiatives and actionable product strategies. Demonstrated expertise in hypothesis generation, experimental design, causal inference, and synthesizing complex data into clear, impactful insights that directly drive product decisions and iteration. Outstanding communication skills, capable of articulating complex technical concepts and strategic recommendations to diverse audiences, including executive leadership, product managers, engineers, instructional designers, and non-technical stakeholders. Strong influencing skills, with the ability to build consensus, navigate organizational complexities, and drive data-informed decisions across cross-functional teams. Highly organized, outcome-oriented, and adept at managing multiple complex projects simultaneously in a fast-paced, agile development environment. Key Technologies & Methodologies: "Product Growth," "A/B Testing," "Experimentation," "Product Strategy," "KPIs," "User Engagement," "Retention," "Causal Inference," "Data Governance," "Ethical AI". Cognitive Diagnostic Model (CDM), Machine Learning, Artificial Intelligence, Mathematician, Statistician, Exploratory Data Analysis (EDA), Computerised Adaptive Testing (CAT), Python /R, SQL, Spark, Multivariate Analysis (SEM, HLM, Bayesian), Visualization tool like PowerBI/Quicksight, Educational Measurement, Simulation Studies.

We’re looking for a hands-on AI Engineer to join our team and build intelligent systems that solve real-world problems at scale. From training deep learning models to deploying them in production, you’ll work across the AI lifecycle — helping us push the boundaries of what machines can do. This is not just a model-tweaking role — we expect you to design solutions, write robust code, and bring models into production with performance and scalability in mind. Key Responsibilities: Design, develop, train, fine-tune, and deploy machine learning / deep learning models. Collaborate with data scientists and engineers to productionize models (model serving, APIs, pipelines). Perform data preprocessing, feature engineering, and model optimization. Build and maintain scalable ML infrastructure using frameworks like TensorFlow, PyTorch, and MLFlow. Apply LLMs, transformers, NLP techniques, or computer vision models based on problem context. Monitor model performance and retrain/refactor as needed in production. Stay up to date with AI research and evaluate potential applications of cutting-edge techniques. Must-Have Skills: Strong coding skills in Python (and ideally experience with C++/Java or other system-level languages). Hands-on experience with ML/DL frameworks: TensorFlow, PyTorch, Hugging Face, Scikit-learn. Experience with NLP, CV, or generative AI techniques (depending on role focus). Solid understanding of model evaluation, training strategies, and overfitting control. Experience working with structured/unstructured data at scale. Familiarity with deploying ML models (REST APIs, Docker, Kubernetes, etc.). Knowledge of cloud platforms (AWS, GCP, or Azure) and MLOps tools is a plus. Good to Have: Experience working with LLMs or foundation models (e.g., OpenAI, LLaMA, Gemini). Familiarity with vector databases (e.g., Pinecone, FAISS) and retrieval-augmented generation (RAG). Exposure to data engineering workflows or real-time inference systems. Contributions to open-source AI/ML projects or strong GitHub portfolio.

Experience : 6.00 + years Salary : INR 3000000-3500000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Hybrid (Pune) Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Daxa, Inc) (*Note: This is a requirement for one of Uplers' client - Daxa, Inc) What do you need for this opportunity? Must have skills required: CI/CD, Database Testing, Docker, Kubernetes, Cloud, Gen AI, Postman, Automation Testing, SaaS, Manual Testing Daxa, Inc is Looking for: Responsibilities Design, develop, and execute comprehensive test strategies for our AI governance SaaS platform, including functional, integration, regression, and performance testing. Test cloud-native GenAI applications, ensuring proper integration with enterprise data and AI security policies. Validate governance policies, access controls, and data compliance workflows. Automate tests using modern test automation frameworks suitable for SaaS environments (e.g., Cypress, Playwright, Selenium, or similar) Perform end-to-end testing of AI workflows—from data ingestion to model retrieval and interaction. Collaborate closely with development team to understand features, use cases, and potential vulnerabilities. Create and maintain detailed test cases, bug reports, and QA documentation. Participate in CI/CD pipeline integration for continuous testing and deployment Contribute to building a scalable, secure, and compliant QA environment for ongoing product evolution. Required Skills And Qualifications. 6+ years of experience in software testing, preferably in cloud-native SaaS or AI/ML platforms. Strong understanding of GenAI applications and common testing challenges around prompt execution, inference outputs, and compliance. Experienced in working with cloud-native applications and GenAI workflows. Experience with cloud platforms (AWS, Azure, or GCP) and containerized applications (Docker, Kubernetes). Familiarity with API testing tools like Postman or RestAssured and Database Testing with MySQL, PostgreSQL and MongoDB. Hands-on experience with test automation frameworks. Exposure to CI/CD pipelines and integration with tools like Jenkins, GitHub Actions, or GitLab CI. Understanding of governance, data lineage, access control, and enterprise security principles is a strong plus. Engagement Model:: Direct placement with the client This is hybrid role. Shift timings ::10 AM to 7 PM How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Audria is a voice-first personal computing device worn discreetly behind the ear. It is designed to be proactive, understands the user’s conversations and provides the user with context-aware personal AI assistance. We’re building something fundamentally new — a privacy-first, voice-first, intelligent system that lives on your device and adapts to you. It requires a blend of machine learning , systems programming , and iOS craftsmanship . Role : iOS Engineer Salary : 12 LPA - 24 LPA fixed (Based on experience) Location : Noida (on-site), 5 days a week Joining date : As soon as possible- July What We’re Looking For Strong iOS fundamentals , especially with Swift , SwiftUI , and modern concurrency (e.g., async/await). Deep comfort working with: AVAudioEngine, Core ML, Core Audio, and low-level iOS APIs. Deep knowledge in: Real-time, low-latency pipelines involving audio , ML inference , and system integration . Familiarity with the on-device ML ecosystem : Core ML, MLX, Metal Performance Shaders (MPS), or any iOS-compatible LLM inference libraries (like llama.cpp or whisper.cpp). Appreciation for systems-level thinking : performance, battery, memory, privacy, background execution, and constraints of mobile hardware. A self-directed builder: able to define their own roadmap, evaluate tradeoffs, and optimize for user experience without needing a spec . Nice to Have Experience working on voice-first or ambient interfaces . Past work with transformers , tokenizers , or LoRA-style adapter architectures . Knowledge of audio classification , VAD , or speech recognition , especially under constrained environments. Contributions to open-source ML or mobile infrastructure projects. Experience integrating or working with C/C++ code in iOS projects (via bridging, SPM, or other methods). The main trait we are looking for when hiring is how fast you can learn new things and execute, as this field is moving fast (Apple Intelligence Foundation Models Framework). We are looking for people who keep up with the latest research and are curious to execute on something promising and challenging.

Key Responsibilities Design and develop advanced generative models including Diffusion Models, GANs, 3D VAEs, and autoregressive models for AI-powered media synthesis. Build and optimize end-to-end content generation pipelines for high-fidelity image, video, and lip-sync generation. Develop multimodal AI systems that integrate speech, video, and facial animation for hyper-realistic content output. Implement and fine-tune models for real-time performance, using techniques such as model quantization, pruning, and distillation. Collaborate with engineering teams to deploy AI models on scalable cloud platforms (AWS, GCP, Azure). Conduct rigorous experimentation to improve model accuracy, realism, and computational efficiency. Stay updated with the latest research in deep generative models, transformer-based vision systems, and multimodal AI. Participate in code reviews, maintain high standards of code quality, and document key findings to support internal knowledge sharing. Requirements Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related field. Minimum 3 years of hands-on experience working with deep generative models (Diffusion Models, GANs, VAEs). Strong proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow. Proven experience in text-to-image, image-to-video, and audio-to-lip-sync model development. Solid understanding of machine learning principles, statistical modeling, and neural network architectures. Familiarity with real-time inference optimization and deployment on cloud environments (AWS, GCP, Azure). Experience working with multimodal architectures and transformer-based models like CLIP, BLIP, or GPT-4V. Contributions to open-source projects or peer-reviewed publications in generative AI, speech synthesis, or video generation are a plus. Key Skills PyTorch AWS Google Cloud Platform (GCP) Azure

Position Overview: We are seeking a talented and motivated AI Engineer with a strong focus on Computer Vision to join our team. The ideal candidate should have a passion for solving complex problems in the field of machine learning and computer vision, as well as the technical expertise required to build and deploy AI solutions. This role is perfect for individuals with 1-4 years of relevant experience, strong programming skills in Python, and a solid understanding of computer vision frameworks and libraries. Key Responsibilities: - Design, develop, and deploy computer vision models to solve real-world problems. - Implement machine learning algorithms for image processing, object detection, segmentation, and recognition tasks. - Optimize and fine-tune models using frameworks like PyTorch and TensorFlow. - Collaborate with cross-functional teams to understand requirements and deliver efficient AI-driven solutions. - Analyze large-scale datasets to derive meaningful insights and improve model performance. - Create and maintain robust, scalable code for production-level AI systems. - Research and stay updated with the latest trends and advancements in computer vision and AI. Required Skills and Qualifications: - Educational Background: Bachelor's or Master’s degree in Computer Science, Data Science, Mathematics, or a related field. - Experience: 1-4 years of hands-on experience in computer vision and machine learning. - Programming Skills: Proficient in Python, with a strong understanding of object-oriented programming and scripting. - Frameworks: Expertise in using PyTorch and TensorFlow for model development and training. - Libraries: Proficient in popular Python libraries such as: - OpenCV-python for computer vision tasks. - Pillow for image processing. - scikit-learn for machine learning and data preprocessing. - Mathematics: Strong foundation in mathematical concepts related to machine learning and computer vision, including: - Linear algebra - Probability and statistics - Calculus - Computer Vision Algorithms: Practical experience in implementing and working with algorithms like: - Object detection - Image classification - Object segmentation - Activity recognition (optional but preferred) - Keypoint detection (optional but preferred) - Familiarity with image annotation tools and dataset preparation techniques. - Experience in version control systems like Git. Preferred Qualifications: - Knowledge of deploying models on edge devices or cloud platforms. - Familiarity with deep learning architectures like CNNs, RNNs, or GANs. - Experience with optimization techniques for model inference speed and accuracy. - Contributions to open-source projects in computer vision or machine learning. If you are passionate about applying AI to solve challenging computer vision problems and have the skills required to excel in this role, we encourage you to apply. Join us in building the next generation of intelligent systems!

Job Title: AI Infrastructure Engineer Experience: 8+ Years Location: Onsite ( Note: The selected candidate is required to relocate to Kovilpatti, Tamil Nadu for the initial three-month project training session . Post training, the candidate will be relocated to one of our onsite locations: Chennai, Hyderabad, or Pune , based on project allocation.) Job Summary: We are looking for an experienced AI Infrastructure Engineer to architect and manage scalable, secure, and high-performance infrastructure tailored for enterprise AI and ML applications. The ideal candidate will collaborate with data scientists, DevOps, and cybersecurity teams to build reliable platforms for efficient model development, training, and deployment. Key Responsibilities: Design and implement end-to-end AI infrastructure using cloud-native tools (Azure, AWS, GCP). Build secure and scalable compute environments with GPU/TPU acceleration for model training and inference. Develop and maintain CI/CD and MLOps pipelines for the AI/ML lifecycle. Optimize large-scale AI workloads using distributed computing and hardware-aware strategies. Manage containerized deployments using orchestration platforms like Kubernetes (AKS, EKS, GKE) and Docker. Ensure system reliability, monitoring, observability, and performance tuning for real-time inference services. Implement automated rollback, logging, and infrastructure monitoring tools. Collaborate with cybersecurity teams to enforce security, data privacy, and regulatory compliance. Technical Skills: Cloud Platforms: Azure Machine Learning, AWS SageMaker, GCP Vertex AI Infrastructure-as-Code: Terraform, ARM Templates, Bicep Containerization & Orchestration: Docker, Kubernetes (AKS, EKS, GKE) MLOps Tools: MLflow, Kubeflow, Azure DevOps, GitHub Actions GPU/TPU Acceleration: CUDA, NVIDIA Triton Inference Server Security & Compliance: TLS, IAM, RBAC, Azure Key Vault Performance: Endpoint scaling, latency optimization, model caching, and resource allocation Qualifications: Bachelor's or Master's in Computer Engineering, Cloud Architecture, or a related field Microsoft Certified: Azure Solutions Architect or DevOps Engineer Expert (preferred) Proven experience deploying and managing large-scale ML pipelines and AI workloads Strong understanding of infrastructure security, networking, and cloud-based AI environments Job Type: Full-time Pay: Up to ₹80,000.00 per month Ability to commute/relocate: Tamulinadu, Tamil Nadu: Reliably commute or willing to relocate with an employer-provided relocation package (Required) Application Question(s): Expected Salary in Annual (INR) Experience: AI Infrastructure Engineer : 8 years (Required) Work Location: In person

Job Title: AI Infrastructure Engineer Experience: 8+ Years *Location: The selected candidate is required to work onsite at our Chennai location for the initial six-month project training and execution period. After the six months , the candidate will be offered remote opportunities.* Job Summary: We are looking for an experienced AI Infrastructure Engineer to architect and manage scalable, secure, and high-performance infrastructure tailored for enterprise AI and ML applications. The ideal candidate will collaborate with data scientists, DevOps, and cybersecurity teams to build reliable platforms for efficient model development, training, and deployment. Key Responsibilities: Design and implement end-to-end AI infrastructure using cloud-native tools (Azure, AWS, GCP). Build secure and scalable compute environments with GPU/TPU acceleration for model training and inference. Develop and maintain CI/CD and MLOps pipelines for the AI/ML lifecycle. Optimize large-scale AI workloads using distributed computing and hardware-aware strategies. Manage containerized deployments using orchestration platforms like Kubernetes (AKS, EKS, GKE) and Docker. Ensure system reliability, monitoring, observability, and performance tuning for real-time inference services. Implement automated rollback, logging, and infrastructure monitoring tools. Collaborate with cybersecurity teams to enforce security, data privacy, and regulatory compliance. Technical Skills: Cloud Platforms: Azure Machine Learning, AWS SageMaker, GCP Vertex AI Infrastructure-as-Code: Terraform, ARM Templates, Bicep Containerization & Orchestration: Docker, Kubernetes (AKS, EKS, GKE) MLOps Tools: MLflow, Kubeflow, Azure DevOps, GitHub Actions GPU/TPU Acceleration: CUDA, NVIDIA Triton Inference Server Security & Compliance: TLS, IAM, RBAC, Azure Key Vault Performance: Endpoint scaling, latency optimization, model caching, and resource allocation Qualifications: Bachelor's or Master's in Computer Engineering, Cloud Architecture, or a related field Microsoft Certified: Azure Solutions Architect or DevOps Engineer Expert (preferred) Proven experience deploying and managing large-scale ML pipelines and AI workloads Strong understanding of infrastructure security, networking, and cloud-based AI environments Job Type: Full-time Pay: Up to ₹80,000.00 per month Ability to commute/relocate: Chennai, Tamil Nadu: Reliably commute or planning to relocate before starting work (Required) Application Question(s): Expected Salary in Annual (INR) Experience: AI Infrastructure Engineer : 8 years (Required) Work Location: In person

Job: Product Manager Location: Bangalore/ Pune Experience: 9 Years to 15Years We are looking for a strategic and technically savvy Product Manager to lead AI-First initiatives within our AINext Platform team. This role focuses on creating scalable, impactful AI solutions by partnering closely with data scientists, engineers, and stakeholders to productize cutting-edge machine learning models and AI capabilities. As the champion of AI-first thinking, you will define and drive the roadmap for AI-powered features, infrastructure, and tools that power intelligent applications across the organization or for external customers. Responsibilities Own the product strategy for AI-first capabilities and features across the applied AI platform. Translate AI research and prototypes into production-ready products by working closely with research, data science, MLOps, and engineering teams. Define requirements for AI services , APIs, and infrastructure needed to support enterprise-scale AI use cases. Collaborate with UX, engineering, and stakeholders to prioritize AI use cases that provide real business value and measurable outcomes. Establish KPIs to measure the impact and performance of AI-driven features , and continuously optimize based on data. Evangelize an “AI-First” mindset across product and business units, helping teams adopt AI as a native capability in their products. Stay on top of the latest AI and ML trends, including foundation models, generative AI, and MLOps best practices. Drive experimentation and model validation pipelines, ensuring reliability, fairness, and explainability in deployed models. Work with responsible AI and compliance teams to ensure all AI initiatives align with ethical, privacy, and regulatory requirements . Qualifications 9+ years of product management experience, preferably in AI/ML or platform products. We have multiple roles requiring higher levels of experience. Strong understanding of machine learning, data science, and modern AI architectures , including LLMs and generative AI. Experience working with or managing AI/ML platforms, such as feature stores, model registries, MLOps pipelines, or inference services. Demonstrated ability to translate complex technical concepts into clear product requirements and business value. Excellent cross-functional communication skills, with experience working across engineering, design, research, and business teams. Familiarity with cloud platforms (AWS, GCP, Azure) and AI infrastructure tools (e.g., MLFlow, Kubeflow, Vertex AI, Databricks, etc.) Experience working in an Agile or Lean product development environment . Experience working with LLMs, embeddings, RAG pipelines, or generative AI tools (e.g., OpenAI, Hugging Face, LangChain). Prior work on B2B SaaS or internal platform products Preferred Qualifications: Technical background (Engineering, or Data Science degree preferred) with MBA preferred. What You’ll Gain: The opportunity to shape the future of AI products at an organization embracing AI-first transformation. A collaborative, forward-thinking environment with access to cutting-edge AI technologies .

Location: Onsite * Note : The selected candidate is required to relocate to Kovilpatti, Tamil Nadu for the initial three-month project training session . Post training, the candidate will be relocated to one of our onsite locations: Chennai, Hyderabad, or Pune , based on project allocation. Job Description The Senior AI Developer will be responsible for designing, building, training, and deploying advanced artificial intelligence and machine learning models to solve complex business challenges across industries. This role demands a strategic thinker and hands-on practitioner who can work at the intersection of data science, software engineering, and innovation. The candidate will contribute to scalable production-grade AI pipelines and mentor junior AI engineers within the Center of Excellence (CoE). Key responsibilities: · Design, train, and fine-tune deep learning models (NLP, CV, LLMs, GANs) for high-value applications · Architect AI model pipelines and implement scalable inference engines in cloud-native environments · Collaborate with data scientists, engineers, and solution architects to productionize ML prototypes · Evaluate and integrate pre-trained models like GPT-4o, Gemini, Claude, and fine-tune based on domain needs · Optimize algorithms for real-time performance, efficiency, and fairness · Write modular, maintainable code and perform rigorous unit testing and validation · Contribute to AI codebase management, CI/CD, and automated retraining infrastructure · Research emerging AI trends and propose innovative applications aligned with business objectives Technical Skills: · Expert in Python, PyTorch, TensorFlow, Scikit-learn, Hugging Face Transformers · LLM deployment & tuning: OpenAI (GPT), Google Gemini, Claude, Falcon, Mistral · Experience with RESTful APIs, Flask/FastAPI for AI service exposure · Proficient in Azure Machine Learning, Databricks, MLflow, Docker, Kubernetes · Hands-on experience with vector databases, prompt engineering, and retrieval-augmented generation (RAG) · Knowledge of Responsible AI frameworks (bias detection, fairness, explainability) Qualification · Master’s in Artificial Intelligence, Machine Learning, Data Science, or Computer Engineering · Certifications in AI/ML (e.g., Microsoft Azure AI Engineer, Google Professional ML Engineer) preferred · Demonstrated success in building scalable AI applications in production environments · Publications or contributions to open-source AI/ML projects are a plus. Job Type: Full-time Pay: Up to ₹80,000.00 per month Location Type: In-person Ability to commute/relocate: Kovilpatti, Tamil Nadu: Reliably commute or willing to relocate with an employer-provided relocation package (Required) Application Question(s): Expected Salary in Annual (INR)? Experience: AI Developer: 8 years (Required) Work Location: In person

Title : Senior AI Developer Experience : 8+ Years *Location: The selected candidate is required to work onsite at our Chennai location for the initial six-month project training and execution period. After the six months , the candidate will be offered remote opportunities.* Job Description The Senior AI Developer will be responsible for designing, building, training, and deploying advanced artificial intelligence and machine learning models to solve complex business challenges across industries. This role demands a strategic thinker and hands-on practitioner who can work at the intersection of data science, software engineering, and innovation. The candidate will contribute to scalable production-grade AI pipelines and mentor junior AI engineers within the Center of Excellence (CoE). Key responsibilities: Design, train, and fine-tune deep learning models (NLP, CV, LLMs, GANs) for high-value applications Architect AI model pipelines and implement scalable inference engines in cloud-native environments Collaborate with data scientists, engineers, and solution architects to productionize ML prototypes Evaluate and integrate pre-trained models like GPT-4o, Gemini, Claude, and fine-tune based on domain needs Optimize algorithms for real-time performance, efficiency, and fairness Write modular, maintainable code and perform rigorous unit testing and validation Contribute to AI codebase management, CI/CD, and automated retraining infrastructure Research emerging AI trends and propose innovative applications aligned with business objectives Technical Skills: Expert in Python, PyTorch, TensorFlow, Scikit-learn, Hugging Face Transformers LLM deployment & tuning: OpenAI (GPT), Google Gemini, Claude, Falcon, Mistral Experience with RESTful APIs, Flask/FastAPI for AI service exposure Proficient in Azure Machine Learning, Databricks, MLflow, Docker, Kubernetes Hands-on experience with vector databases, prompt engineering, and retrieval-augmented generation (RAG) Knowledge of Responsible AI frameworks (bias detection, fairness, explainability) Qualification Master’s in Artificial Intelligence, Machine Learning, Data Science, or Computer Engineering Certifications in AI/ML (e.g., Microsoft Azure AI Engineer, Google Professional ML Engineer) preferred Demonstrated success in building scalable AI applications in production environments Publications or contributions to open-source AI/ML projects are a plus. Job Type: Full-time Pay: Up to ₹80,000.00 per month Location Type: In-person Ability to commute/relocate: Chennai, Tamil Nadu: Reliably commute or planning to relocate before starting work (Required) Application Question(s): Expected Salary in Annual (INR)? Experience: AI Developer: 8 years (Required) Work Location: In person

Company Description Echoleads.ai leverages AI-powered sales agents to engage, qualify, and convert leads through real-time voice conversations. Our voice bots act as scalable sales representatives, making thousands of smart, human-like calls daily to follow up instantly, ask the right questions, and book appointments effortlessly. Echoleads integrates seamlessly with lead sources like Meta Ads, Google Ads, and CRMs, ensuring leads are never missed. Serving modern sales and marketing teams across various industries, our AI agents proficiently handle outreach, lead qualification, and appointment setting. About the Role: We are seeking a highly experienced Voice AI /ML Engineer to lead the design and deployment of real-time voice intelligence systems. This role focuses on ASR, TTS, speaker diarization, wake word detection, and building production-grade modular audio processing pipelines to power next-generation contact center solutions, intelligent voice agents, and telecom-grade audio systems. You will work at the intersection of deep learning, streaming infrastructure, and speech/NLP technology, creating scalable, low-latency systems across diverse audio formats and real-world applications. Key Responsibilities: Voice & Audio Intelligence: Build, fine-tune, and deploy ASR models (e.g., Whisper, wav2vec2.0, Conformer) for real-time transcription. Develop and finetune high-quality TTS systems using VITS, Tacotron, FastSpeech for lifelike voice generation and cloning. Implement speaker diarization for segmenting and identifying speakers in multi-party conversations using embeddings (x-vectors/d-vectors) and clustering (AHC, VBx, spectral clustering). Design robust wake word detection models with ultra-low latency and high accuracy in noisy conditions. Real-Time Audio Streaming & Voice Agent Infrastructure: Architect bi-directional real-time audio streaming pipelines using WebSocket, gRPC, Twilio Media Streams, or WebRTC. Integrate voice AI models into live voice agent solutions, IVR automation, and AI contact center platforms. Optimize for latency, concurrency, and continuous audio streaming with context buffering and voice activity detection (VAD). Build scalable microservices to process, decode, encode, and stream audio across common codecs (e.g., PCM, Opus, μ-law, AAC, MP3) and containers (e.g., WAV, MP4). Deep Learning & NLP Architecture: Utilize transformers, encoder-decoder models, GANs, VAEs, and diffusion models, for speech and language tasks. Implement end-to-end pipelines including text normalization, G2P mapping, NLP intent extraction, and emotion/prosody control. Fine-tune pre-trained language models for integration with voice-based user interfaces. Modular System Development: Build reusable, plug-and-play modules for ASR, TTS, diarization, codecs, streaming inference, and data augmentation. Design APIs and interfaces for orchestrating voice tasks across multi-stage pipelines with format conversions and buffering. Develop performance benchmarks and optimize for CPU/GPU, memory footprint, and real-time constraints. Engineering & Deployment: Writing robust, modular, and efficient Python code Experience with Docker, Kubernetes, cloud deployment (AWS, Azure, GCP) Optimize models for real-time inference using ONNX, TorchScript, and CUDA, including quantization, context-aware inference, model caching. On device voice model deployment.

Designation: Senior Analyst – Data Science Level: L2 Experience: 3 to 6 years Location: Chennai Job Description: We are seeking a highly skilled and motivated Senior Analyst candidate with 3-6 years of experience in Data Science to join our growing team. Responsibilities: Perform analyses on products to answer open-ended questions and provide strategic recommendations. Design and guide experiments/analysis to measure impact and drive product improvements. Develop and maintain key metrics and reports, enhancing data infrastructure for better analysis. Skills: At least a BA/BS in a quantitative field (ex Math, Stats, Physics, or Computer Science) with 2+ years of relevant experience. Key Skillsets looking for: SQL, Python, BI, Statistics, A/B testing, Data Science, Machine Learning Experience driving impact for a digital product with an iterative development cycle. Understanding of statistical concepts and practical experience applying them (in A|B testing, causal inference, ML, etc.). Experience in data analyses using SQL. Experience in programming/modeling in Python. Demonstration of our core cultural values: clear communication, positive energy, continuous learning, and efficient execution. Job Snapshot Updated Date 02-07-2025 Job ID J_3824 Location Chennai, Tamil Nadu, India Experience 3 - 6 Years Employee Type Permanent

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together. We are seeking a skilled and motivated AI/ML Engineer with 3-5 years of experience to join our team. The ideal candidate will have hands-on expertise in building and deploying AI/ML solutions on the Azure platform, with a solid focus on Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) systems, and Azure ML Studio. You will play a key role in designing intelligent systems, deploying scalable models, and integrating advanced AI capabilities into enterprise applications. Primary Responsibilities AI/ML Development & Deployment: Design, develop, and deploy machine learning models using Azure ML Studio and Azure Machine Learning services Build and fine-tune LLM-based solutions for enterprise use cases Develop and implement RAG pipelines using Azure services and vector databases Deploy and monitor AI/ML models in production environments ensuring scalability and performance Azure Platform Engineering: Leverage Azure services such as Azure Data Lake, Azure Synapse, Azure Blob Storage, and Azure Cognitive Search for data ingestion and processing Integrate AI models with Azure-based data pipelines and APIs Use Azure DevOps for CI/CD of ML workflows and model versioning Data Engineering & Processing: Build and maintain ETL/ELT pipelines for structured and unstructured data using Databricks and Apache Spark Prepare and transform data for training and inference using Python, PySpark and SQL LLM & RAG System Implementation: Implement LLM-based agents and chatbots using frameworks like Langchain Design and optimize RAG architectures for domain-specific knowledge retrieval Work with vector databases (e.g., Azure Cognitive Search, FAISS) for embedding-based search Collaboration & Innovation: Collaborate with data scientists, product managers, and engineers to deliver AI-driven features Stay current with advancements in generative AI, LLMs, and Azure AI services Contribute to the continuous improvement of AI/ML pipelines and best practices Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so 3+ years of hands-on experience in AI/ML engineering with a focus on Azure Proven experience in deploying ML models using Azure ML Studio and Azure Machine Learning Experience working with LLMs, RAG systems, and AI agents Experience with Databricks, Apache Spark, and Azure Data services Knowledge of Azure DevOps and CI/CD for ML workflows Understanding of data governance and security in cloud environments Familiarity with MLOps practices and model monitoring tools Familiarity with vector databases and embedding models Proficiency in Python, SQL, and PySpark Proven solid analytical and problem-solving skills Proven effective communication and collaboration with cross-functional teams Proven ability to translate business requirements into technical solutions At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes — an enterprise priority reflected in our mission.

Who We Are Zinnia is the leading technology platform for accelerating life and annuities growth. With innovative enterprise solutions and data insights, Zinnia simplifies the experience of buying, selling, and administering insurance products. All of which enables more people to protect their financial futures. Our success is driven by a commitment to three core values: be bold, team up, deliver value – and that we do. Zinnia has over $180 billion in assets under administration, serves 100+ carrier clients, 2500 distributors and partners, and over 2 million policyholders. Who You Are We are seeking a highly motivated Senior Data Analyst with strong technical expertise, business acumen, and strategic problem-solving abilities . In this role, you will independently own and drive analytics initiatives within the Operations team , translating data into actionable insights that improve efficiency, decision-making, and key business KPIs. You will work closely with stakeholders across Operations, Product, Data Engineering, and Business Strategy to identify opportunities for process optimization, automate decision-making, and create scalable analytics frameworks. This is a high-impact individual contributor role that requires both deep analytical skills and the ability to influence business strategy through data. What You’ll Do Drive analytics strategy: Independently own and drive key analytics initiatives in Operations, proactively identifying areas for efficiency improvements and cost optimization. Advanced analytics & measurement: Move beyond basic dashboards and leverage inferential modeling, causal analysis, and experimental design to generate actionable insights. Experimentation & testing: Design and implement A/B tests to measure the impact of operational improvements, optimizing key processes such as fraud detection, customer interactions, and compliance. Operational KPIs & business impact: Develop frameworks to measure Turnaround Time (TAT), Cost Per Transaction, SLA adherence, and other key operational metrics, ensuring data-driven decision-making. Data storytelling & visualization: Translate complex data insights into clear, actionable recommendations using visual storytelling techniques in Power BI and other visualization tools. Cross-functional collaboration: Work closely with stakeholders across Operations, Data Engineering, and Product to align analytics initiatives with business needs. Scalability & automation: Partner with Data Engineering to enhance data pipelines, data models, and automation efforts that improve efficiency and reduce manual work. Thought leadership & best practices: Drive data analysis best practices and mentor junior analysts, fostering a culture of analytical rigor and excellence. What You’ll Need 5+ years of experience in data analytics, with a focus on Operations, Business Strategy, or Process Optimization. Expertise in SQL, Python and with a strong ability to work with relational cloud databases (Redshift, BigQuery, Snowflake) and unstructured datasets. Experience designing A/B tests and experimentation frameworks to drive operational improvements. Strong statistical knowledge, including regression analysis, time-series forecasting, and causal inference modeling. Experience in operations analytics such as workforce efficiency, process optimization, risk modeling, and compliance analytics. Hands-on experience with data visualization tools (Power BI, Tableau, Looker) and the ability to present insights effectively to leadership. Ability to work independently, take ownership of projects, and influence business decisions through data-driven recommendations. Strong problem-solving skills and a proactive mindset to identify business opportunities using data Bonus Points If You Have Experience with ML/AI applications in operational efficiency (e.g., anomaly detection, predictive modeling, workforce automation). Familiarity with event-tracking frameworks and behavioral analytics. Strong data storytelling skills—can translate complex data into concise, compelling narratives. Prior experience in a fast-paced, high-growth environment with a focus on scaling data analytics. WHAT’S IN IT FOR YOU? At Zinnia, you collaborate with smart, creative professionals who are dedicated to delivering cutting-edge technologies, deeper data insights, and enhanced services to transform how insurance is done. Visit our website at www.zinnia.com for more information. Apply by completing the online application on the careers section of our website. We are an Equal Opportunity employer committed to a diverse workforce. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability.

Role As a Data Scientist, you will contribute to developing and deploying innovative AI and machine learning solutions that transform insurance operations through intelligent automation. You'll work on sophisticated models for Fraud, Waste & Abuse (FWA) detection, Intelligent Document Processing (IDP), and Agentic AI systems that power autonomous insurance workflows including underwriting, claims processing, and policy servicing. This role offers excellent opportunities for growth and learning - you'll contribute to core product development, support customer implementations, and assist with proof-of-concept development under the guidance of senior team members. Working with our advanced tech stack including LLM fine-tuning, computer vision, and multi-agent systems, you'll solve complex problems that directly impact how insurance companies operate and serve their customers. As we scale from successful startup to enterprise-level positioning, you'll develop your expertise in production machine learning, learn best practices from experienced practitioners, and contribute meaningfully to AI solutions that maintain the highest standards of accuracy, reliability, and business impact. If you're passionate about applying data science to real-world insurance challenges and want to grow your career while seeing your models transform business processes, this role offers excellent opportunities for professional development. Model Development & Implementation Develop and implement machine learning models for fraud detection, risk assessment, and anomaly detection using established algorithms and frameworks under senior guidance Build computer vision and NLP models for intelligent document processing, including document classification, OCR optimization, and automated information extraction Implement and fine-tune Large Language Models (LLMs) for insurance-specific applications, applying techniques such as LoRA, QLoRA, and PEFT to create domain-specialized solutions Develop predictive models for underwriting, claims processing, and medical risk assessment that support enhanced decision-making and operational efficiency Perform feature engineering and exploratory data analysis to identify patterns and insights that inform model development and business understanding AI Agent Development & Support Contribute to the development of autonomous AI agents for handling insurance workflows with appropriate supervision and guidance Implement agent components and workflows that support multi-agent coordination and decision-making processes Build conversational AI capabilities that can interact with users and systems to gather information and provide recommendations Support the development of intelligent decision-making systems that adapt to varying business requirements and regulatory constraints Assist with the implementation of agent monitoring, evaluation, and improvement processes Data Processing & Analysis Build and maintain data pipelines for model training, validation, and inference using modern data engineering tools and practices Implement data quality checks and validation processes that ensure model inputs meet accuracy and consistency requirements Perform comprehensive data analysis to understand data characteristics, identify quality issues, and inform model development decisions Create data visualizations and analytical reports that communicate insights to technical and business stakeholders Work with diverse data sources including structured insurance data, unstructured documents, and external data feeds Model Deployment & Monitoring Support Support model deployment processes from development through production, working with MLOps teams to ensure smooth transitions Implement model monitoring and performance tracking capabilities that detect issues and support continuous improvement Contribute to A/B testing and model evaluation frameworks that enable data-driven decisions about model performance Develop model documentation and explainability features that support business understanding and regulatory compliance Participate in model maintenance and improvement activities based on production performance and business feedback Collaboration & Learning Work closely with senior data scientists, solution architects, and software engineers to deliver high-quality technical solutions Support customer-facing activities by adapting models for specific client needs and contributing to implementation success Contribute to proof-of-concept development and technical demonstrations that Showcase Our Capabilities To Prospective Customers Participate in code reviews, technical discussions, and knowledge sharing activities that support team learning and best practices Stay current with emerging trends and techniques in AI/ML, particularly in areas relevant to insurance and autonomous agents Qualifications & Experience Academic Qualifications Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or related quantitative field from a recognized institution Coursework or training in machine learning, statistics, or data analysis preferred Professional Experience 3+ years of hands-on experience in data science, machine learning, or related analytical roles with demonstrated ability to develop and deploy ML models Experience with machine learning project lifecycle from data exploration through model deployment Background in applying statistical methods and machine learning algorithms to solve business problems Exposure to production ML systems, model deployment, or MLOps practices Preferred Insurance industry exposure preferred, with understanding of claims processing, underwriting, medical risk assessment, or fraud detection workflows Technical Skills Strong proficiency in Python with experience using Scikit-Learn, Pandas, NumPy, and Jupyter for data science workflows Experience with machine learning frameworks such as TensorFlow, PyTorch, or similar libraries for model development Basic to intermediate knowledge of LLM fine-tuning, natural language processing, or computer vision techniques. Understanding of embeddings, TF-IDF, and linguistic modelling. Familiarity with OCR technologies, document processing, or computer vision libraries such as OpenCV Experience with GenAI frameworks including LangChain, Hugging Face Transformers, or vector databases Knowledge of data manipulation and analysis using SQL, big data tools, or distributed computing frameworks Understanding of MLOps concepts, version control systems, and basic cloud platform usage Communication & Collaboration Skills Strong analytical and problem-solving skills with ability to approach complex business problems systematically Good communication abilities for presenting technical findings to team members and stakeholders Collaborative mindset with willingness to learn from senior team members and contribute to team success Attention to detail and commitment to producing high-quality, reliable analytical work Enthusiasm for learning new technologies and staying current with developments in AI/ML and insurance technology How We Get Things Done At our core, we believe in building intelligent systems that transform how insurance works. We're a team of innovators who combine deep technical expertise with real-world business impact. Our guiding principles center around technical excellence, data-driven decision making, and the responsible development of AI systems that enhance human capabilities. We foster a culture of continuous learning, experimentation, and cross-functional collaboration. As we scale from startup to enterprise, we maintain our commitment to cutting-edge research while building solutions that can handle the most demanding insurance workflows globally. Championing Inclusion & Innovation We embrace the opportunity to build a team that reflects diverse perspectives and experiences. Being an equal opportunity employer means we consider qualified candidates based on merit, technical capabilities, and cultural fit, regardless of background, identity, or personal characteristics. We're committed to creating an inclusive environment where innovative thinking thrives and where every team member can contribute to our mission of transforming insurance through intelligent automation. Skills: ml,processing,python,sql,pandas,pytorch,insurance,numpy,ocr technologies,data,machine learning,data science,learning,genai frameworks,scikit-learn,tensorflow,computer vision,data analysis,natural language processing,mlops,jupyter

Role As a Data Scientist, you will contribute to developing and deploying innovative AI and machine learning solutions that transform insurance operations through intelligent automation. You'll work on sophisticated models for Fraud, Waste & Abuse (FWA) detection, Intelligent Document Processing (IDP), and Agentic AI systems that power autonomous insurance workflows including underwriting, claims processing, and policy servicing. This role offers excellent opportunities for growth and learning - you'll contribute to core product development, support customer implementations, and assist with proof-of-concept development under the guidance of senior team members. Working with our advanced tech stack including LLM fine-tuning, computer vision, and multi-agent systems, you'll solve complex problems that directly impact how insurance companies operate and serve their customers. As we scale from successful startup to enterprise-level positioning, you'll develop your expertise in production machine learning, learn best practices from experienced practitioners, and contribute meaningfully to AI solutions that maintain the highest standards of accuracy, reliability, and business impact. If you're passionate about applying data science to real-world insurance challenges and want to grow your career while seeing your models transform business processes, this role offers excellent opportunities for professional development. Model Development & Implementation Develop and implement machine learning models for fraud detection, risk assessment, and anomaly detection using established algorithms and frameworks under senior guidance Build computer vision and NLP models for intelligent document processing, including document classification, OCR optimization, and automated information extraction Implement and fine-tune Large Language Models (LLMs) for insurance-specific applications, applying techniques such as LoRA, QLoRA, and PEFT to create domain-specialized solutions Develop predictive models for underwriting, claims processing, and medical risk assessment that support enhanced decision-making and operational efficiency Perform feature engineering and exploratory data analysis to identify patterns and insights that inform model development and business understanding AI Agent Development & Support Contribute to the development of autonomous AI agents for handling insurance workflows with appropriate supervision and guidance Implement agent components and workflows that support multi-agent coordination and decision-making processes Build conversational AI capabilities that can interact with users and systems to gather information and provide recommendations Support the development of intelligent decision-making systems that adapt to varying business requirements and regulatory constraints Assist with the implementation of agent monitoring, evaluation, and improvement processes Data Processing & Analysis Build and maintain data pipelines for model training, validation, and inference using modern data engineering tools and practices Implement data quality checks and validation processes that ensure model inputs meet accuracy and consistency requirements Perform comprehensive data analysis to understand data characteristics, identify quality issues, and inform model development decisions Create data visualizations and analytical reports that communicate insights to technical and business stakeholders Work with diverse data sources including structured insurance data, unstructured documents, and external data feeds Model Deployment & Monitoring Support Support model deployment processes from development through production, working with MLOps teams to ensure smooth transitions Implement model monitoring and performance tracking capabilities that detect issues and support continuous improvement Contribute to A/B testing and model evaluation frameworks that enable data-driven decisions about model performance Develop model documentation and explainability features that support business understanding and regulatory compliance Participate in model maintenance and improvement activities based on production performance and business feedback Collaboration & Learning Work closely with senior data scientists, solution architects, and software engineers to deliver high-quality technical solutions Support customer-facing activities by adapting models for specific client needs and contributing to implementation success Contribute to proof-of-concept development and technical demonstrations that Showcase Our Capabilities To Prospective Customers Participate in code reviews, technical discussions, and knowledge sharing activities that support team learning and best practices Stay current with emerging trends and techniques in AI/ML, particularly in areas relevant to insurance and autonomous agents Qualifications & Experience Academic Qualifications Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or related quantitative field from a recognized institution Coursework or training in machine learning, statistics, or data analysis preferred Professional Experience 3+ years of hands-on experience in data science, machine learning, or related analytical roles with demonstrated ability to develop and deploy ML models Experience with machine learning project lifecycle from data exploration through model deployment Background in applying statistical methods and machine learning algorithms to solve business problems Exposure to production ML systems, model deployment, or MLOps practices Preferred Insurance industry exposure preferred, with understanding of claims processing, underwriting, medical risk assessment, or fraud detection workflows Technical Skills Strong proficiency in Python with experience using Scikit-Learn, Pandas, NumPy, and Jupyter for data science workflows Experience with machine learning frameworks such as TensorFlow, PyTorch, or similar libraries for model development Basic to intermediate knowledge of LLM fine-tuning, natural language processing, or computer vision techniques. Understanding of embeddings, TF-IDF, and linguistic modelling. Familiarity with OCR technologies, document processing, or computer vision libraries such as OpenCV Experience with GenAI frameworks including LangChain, Hugging Face Transformers, or vector databases Knowledge of data manipulation and analysis using SQL, big data tools, or distributed computing frameworks Understanding of MLOps concepts, version control systems, and basic cloud platform usage Communication & Collaboration Skills Strong analytical and problem-solving skills with ability to approach complex business problems systematically Good communication abilities for presenting technical findings to team members and stakeholders Collaborative mindset with willingness to learn from senior team members and contribute to team success Attention to detail and commitment to producing high-quality, reliable analytical work Enthusiasm for learning new technologies and staying current with developments in AI/ML and insurance technology How We Get Things Done At our core, we believe in building intelligent systems that transform how insurance works. We're a team of innovators who combine deep technical expertise with real-world business impact. Our guiding principles center around technical excellence, data-driven decision making, and the responsible development of AI systems that enhance human capabilities. We foster a culture of continuous learning, experimentation, and cross-functional collaboration. As we scale from startup to enterprise, we maintain our commitment to cutting-edge research while building solutions that can handle the most demanding insurance workflows globally. Championing Inclusion & Innovation We embrace the opportunity to build a team that reflects diverse perspectives and experiences. Being an equal opportunity employer means we consider qualified candidates based on merit, technical capabilities, and cultural fit, regardless of background, identity, or personal characteristics. We're committed to creating an inclusive environment where innovative thinking thrives and where every team member can contribute to our mission of transforming insurance through intelligent automation. Skills: ml,processing,python,sql,pandas,pytorch,insurance,numpy,ocr technologies,data,machine learning,data science,learning,genai frameworks,scikit-learn,tensorflow,computer vision,data analysis,natural language processing,mlops,jupyter

Summary JOB DESCRIPTION The Sr Financial Analyst will exhibit genuine interest in solving work problems through proactively asking questions, clearly communicating and collaborating both internally and externally to grow the business. In addition, the Financial Analyst is responsible for understanding our competition and customers and showing initiative to learn and continuously improve company processes. The Sr Financial Analyst will be responsible for long term planning, financial analysis and business analysis. The Sr Financial Analyst will play an integral role in the success of the company and our clients. Duties & Responsibilities Listed in order of relevance: Financial Planning and Analysis: Develop financial statement forecasts, create and maintain financial dashboards, and perform financial analysis to support decision-making. Operational Excellence: Ensure internal controls are in place to protect the global asset base, meet enterprise planning and financial reporting requirements on a US GAAP basis, and lead fiduciary roles Business Forecasting: Develop and maintain automated forecasting processes, scorecard forecasting processes, and implement enhancements to deliver targeted precision Reporting and Analysis: Provide critical insights, serve as a financial advisor to finance leaders, and establish and maintain data integrity. Month-End Close Process: Manage the month-end close process, including reviewing ISC Key Metrics and summaries at various levels of operations. Inventory Management: Establish a consistent methodology for determining if costs contribute to the production of inventory and performing variance analysis vs AOP Standardized Reporting: Deploy standardized and digitized reporting, connect ISC EDW and Digital Finance for holistic reporting, and create standard FDS smart view pulls to validate data. Execute ISC Finance objectives, drive results, hold others accountable to their commitments, and maintain an operational excellence culture Investigate / resolve any issues or errors related to the finance side of the ERP system Month end financial responsibilities (JE’s, Accrual entries, etc) with USA entity Responsible for updating/monitoring standard costs each year for all entities and providing year-end Inventory reports Respond to change productively and handle other duties as required. Follow all company safety policies and procedures. Education & Experience Strong Excel, PowerPoint and Access skills, with particular focus on financial modeling and the use of advanced features of spreadsheets. Experience with financial modeling. High level of analytical ability and accuracy. Highly organized and ability to work on multiple projects at once. Ability to work independently and complete tasks with minimal supervision. Excellent interpersonal and organization skills required. A bachelor’s degree in accounting, finance or a related field plus 5 years or more of job-related experience; the equivalent combination of training and experience may be suitable; a CPA and/or MBA is preferred. Responsibilities KNOWLEDGE & SKILLS Ability to read, analyze, and interpret general business periodicals, professional journals, technical procedures, or governmental regulations. Ability to write reports, business correspondence, and procedure manuals. Ability to effectively present information and respond to questions from groups of managers, clients, customers, and the general public. Ability to work with mathematical concepts such as probability and statistical inference, and fundamentals of plane and solid geometry and trigonometry. Ability to define problems, collect data, establish facts, and draw valid conclusions. Ability to interpret an extensive variety of technical instructions in mathematical or diagram form and deal with several abstract and concrete variables. Proficiency in MS Office applications (MS Word, MS Excel, MS Access, MS PowerPoint, MS Outlook). Ability to read, speak, and write in English required. About Us Honeywell helps organizations solve the world's most complex challenges in automation, the future of aviation and energy transition. As a trusted partner, we provide actionable solutions and innovation through our Aerospace Technologies, Building Automation, Energy and Sustainability Solutions, and Industrial Automation business segments – powered by our Honeywell Forge software – that help make the world smarter, safer and more sustainable.

Mandatory Skills - Gen-AI, Data Science, Python, RAG and Cloud (AWS/Azure) Secondary - Machine Learning, Deep Learning, ChatGPT, Langchain, Prompt, vector stores, RAG, llama, Computer vision, Deep learning, Machine learning, OCR, Transformer, regression, forecasting, classification, hyper parameter tunning, MLOps, Inference, Model training, Model Deployment. Job Description More than 6 years of experience in Data Engineering, Data Science and AI / ML domain Excellent understanding of machine learning techniques and algorithms, such as GPTs, CNN, RNN, k-NN, Naive Bayes, SVM, Decision Forests, etc. Experience using business intelligence tools (e.g. Tableau, PowerBI) and data frameworks (e.g. Hadoop) Experience in Cloud native skills. Knowledge of SQL and Python; familiarity with Scala, Java or C++ is an asset Analytical mind and business acumen and Strong math skills (e.g. statistics, algebra) Experience with common data science toolkits, such as TensorFlow, KERAs, PyTorch, PANDAs, Microsoft CNTK, NumPy etc. Deep expertise in at least one of these is highly desirable. Experience with NLP, NLG and Large Language Models like – BERT, LLaMa, LaMDA, GPT, BLOOM, PaLM, DALL-E, etc. Great communication and presentation skills. Should have experience in working in a fast-paced team culture. Experience with AIML and Big Data technologies like – AWS SageMaker, Azure Cognitive Services, Google Colab, Jupyter Notebook, Hadoop, PySpark, HIVE, AWS EMR etc. Experience with NoSQL databases, such as MongoDB, Cassandra, HBase, Vector databases Good understanding of applied statistics skills, such as distributions, statistical testing, regression, etc. Should be a data-oriented person with analytical mind and business acumen.