1480 Mlflow Jobs - Page 22

Skill Set Required: 2–7 years of experience in software engineering and ML development. Strong proficiency in Python and ML libraries such as Scikit-learn, TensorFlow, or PyTorch. Experience building and evaluating models, along with data preprocessing and feature engineering. Proficiency in REST APIs, Docker, Git, and CI/CD tools. Solid foundation in software engineering principles, including data structures, algorithms, and design patterns. Hands-on experience with MLOps platforms (e.g., MLflow, TFX, Airflow, Kubeflow). Exposure to NLP, large language models (LLMs), or computer vision projects. Experience with cloud platforms (AWS, GCP, Azure) and managed ML services. Contributions to open-source ML libraries or participation in ML competitions (e.g., Kaggle, DrivenData) is a plus.

About HYI.AI HYI.AI is a Virtual Assistance and GenAI platform built for startups, entrepreneurs, and tech innovators. We specialize in offering virtual talent solutions, GenAI tools, and custom AI/ML deployments to help founders and businesses scale smarter and faster. We’re on a mission to power the next wave of digital startups globally - and we’re looking for talented Full Stack Developers to join us remotely. Role Overview We are seeking an experienced Data Science Engineer to build intelligent systems that deliver business impact through data. You will work at the intersection of engineering and applied science - developing machine learning models, deploying them into production, and ensuring they operate at scale. This freelance role is ideal for professionals who bring both statistical rigor and software engineering depth to real-world problems. Key Responsibilities Design, build, and deploy machine learning models for real-time and batch applications Process and analyze large datasets to extract actionable insights Develop data pipelines and model workflows in production environments Work with product teams to frame data science solutions for business use cases Monitor model performance, retraining, and drift over time Communicate findings through clear visualizations, documentation, and reports What We’re Looking For Experience in data science, machine learning, or applied analytics Strong background in statistics, data structures, and algorithms Proficiency in Python (Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch) Experience building end-to-end ML workflows, from exploration to deployment Familiarity with cloud platforms (AWS, GCP, or Azure) and MLOps practices Ability to work independently and translate ambiguous problems into scalable solutions Preferred Skills Experience with tools like Airflow, MLflow, or Kubeflow Working knowledge of SQL and NoSQL databases Exposure to big data tools (Spark, Hadoop, Dask) Knowledge of model versioning, monitoring, and explainability techniques Experience in domains like NLP, computer vision, or time series analysis is a plus What You’ll Gain Collaborate with forward-thinking startups on data-driven challenges Flexible work hours and remote-first engagements Autonomy to lead technical decisions and build intelligent systems Be part of an exclusive network of top-tier data and tech professionals

Job Title: AI/ML Engineer Location: 100% Remote Job Type: Full-Time About the Role: We are seeking a highly skilled and motivated AI/ML Engineer to design, develop, and deploy cutting-edge ML models and data-driven solutions. You will work closely with data scientists, software engineers, and product teams to bring AI-powered products to life and scale them effectively. Key Responsibilities: Design, build, and optimize machine learning models for classification, regression, recommendation, and NLP tasks. Collaborate with data scientists to transform prototypes into scalable, production-ready models. Deploy, monitor, and maintain ML pipelines in production environments. Perform data preprocessing, feature engineering, and selection from structured and unstructured data. Implement model performance evaluation metrics and improve accuracy through iterative tuning. Work with cloud platforms (AWS, Azure, GCP) and MLOps tools to manage model lifecycle. Maintain clear documentation and collaborate cross-functionally across teams. Stay updated with the latest ML/AI research and technologies to continuously enhance our solutions. Required Qualifications: Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field. 2–5 years of experience in ML model development and deployment. Proficient in Python and libraries such as scikit-learn, TensorFlow, PyTorch, pandas, NumPy, etc. Strong understanding of machine learning algorithms, statistical modeling, and data analysis. Experience with building and maintaining ML pipelines using tools like MLflow, Kubeflow, or Airflow. Familiarity with containerization (Docker), version control (Git), and CI/CD for ML models. Experience with cloud services such as AWS SageMaker, GCP Vertex AI, or Azure ML.

Location Mumbai, Maharashtra, 400063 Category Engineering / Information Technology Job Type Full time Job Id 1183231 No AI ML Engineer This role has been designed as ‘’Onsite’ with an expectation that you will primarily work from an HPE partner/customer office. Who We Are: Hewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today’s complex world. Our culture thrives on finding new and better ways to accelerate what’s next. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good. If you are looking to stretch and grow your career our culture will embrace you. Open up opportunities with HPE. Job Description: HPE Operations is our innovative IT services organization. It provides the expertise to advise, integrate, and accelerate our customers’ outcomes from their digital transformation. Our teams collaborate to transform insight into innovation. In today’s fast paced, hybrid IT world, being at business speed means overcoming IT complexity to match the speed of actions to the speed of opportunities. Deploy the right technology to respond quickly to market possibilities. Join us and redefine what’s next for you. What you’ll do: Key responsibilities of a Technical Consultant may include. Delivery of Data Analytics and AI solutions in enterprise and mission-critical customers. Assess and appreciate technical issues and customers' business impact. Troubleshooting and resolving issues with Data Analytics and AI solution stack delivered to customers. Technical delivery and support of support of Kubernetes (K8s) environments, and well-versed in data processing and AI toolings Fault isolation, Problem reproduction, interacting with the engineering teams, QA, and development partners. Escalation and Elevation management Development of knowledge content and runbooks Knowledge & Skills Required 1 to 2 years of relevant experience after Engineering (B.Tech / MCA / M.Tech) degree. Good understanding of AI/ML and Data Analytics applications on a few of the solution stacks such as : Kubeflow & MLflow, MLOPS framework Apache Spark and Superset Data Lake NVIDIA AI Enterprise NIM Microservices, NeMo modules MLDE (Determined AI) Good understand and knowledge on a few of the below platform components Hands-on experience in any of the Linux operating system (RHEL 8/Rocky/Ubuntu/Centos/Suse) OS, Networking & Virtualization; Good understanding of VMware vCenter + ESXi 7 & 8, , Switching. Layer 2 Networking, Cluster management - HA, DRS NFS storage configuration and troubleshooting would be desired Knowledge and experience with Linux System Administration, package management, scheduling, boot procedures/troubleshooting, performance optimization, and networking concepts. Windows AD administration (user management & authentication) Kubernetes, container runtimes and Container networking, Creating Docker Images. Familiarlity of deployment using Docker and Kubernetes on GPU-powered systems. Hpe Ezmeral-specific Kubernetes Single Sign-on and IAM Postgres database Helm, Istio and Spire Storage and CSI, CNI, operators (File Storage/ Block Storage/Object Storage) NVIDIA GPU, NVIDIA AI and related software’s Good GPU Understanding and troubleshooting skills at the HW, OS, SW and Application layers. Optional experience with cloud platforms such as AWS, Azure, or Google Cloud for NVIDIA GPU-based AI model deployment. Additional Skills: Accountability, Accountability, Active Learning (Inactive), Active Listening, Bias, Business Growth, Client Expectations Management, Coaching, Creativity, Critical Thinking, Cross-Functional Teamwork, Customer Centric Solutions, Customer Relationship Management (CRM), Design Thinking, Empathy, Follow-Through, Growth Mindset, Information Technology (IT) Infrastructure, Infrastructure as a Service (IaaS), Intellectual Curiosity (Inactive), Long Term Planning, Managing Ambiguity, Process Improvements, Product Services, Relationship Building {+ 5 more} What We Can Offer You: Health & Wellbeing We strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their physical, financial and emotional wellbeing. Personal & Professional Development We also invest in your career because the better you are, the better we all are. We have specific programs catered to helping you reach any career goals you have — whether you want to become a knowledge expert in your field or apply your skills to another division. Unconditional Inclusion We are unconditionally inclusive in the way we work and celebrate individual uniqueness. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good. Let's Stay Connected: Follow @HPECareers on Instagram to see the latest on people, culture and tech at HPE. #india #operations Job: Services Job Level: TCP_01 HPE is an Equal Employment Opportunity/ Veterans/Disabled/LGBT employer. We do not discriminate on the basis of race, gender, or any other protected category, and all decisions we make are made on the basis of qualifications, merit, and business need. Our goal is to be one global team that is representative of our customers, in an inclusive environment where we can continue to innovate and grow together. Please click here: Equal Employment Opportunity. Hewlett Packard Enterprise is EEO Protected Veteran/ Individual with Disabilities. HPE will comply with all applicable laws related to employer use of arrest and conviction records, including laws requiring employers to consider for employment qualified applicants with criminal histories.

Job Information Date Opened 07/01/2025 Job Type Full time Industry Technology Work Experience 5+ years City Chennai State/Province Tamil Nadu Country India Zip/Postal Code 600096 Job Description Job Description: Job Summary: We are looking for a skilled and driven Machine Learning Engineer with 4+ years of experience to design, develop, and deploy ML solutions across business-critical applications. You’ll work alongside data scientists, software engineers, and product teams to create scalable, high-impact machine learning systems in production environments. Key Responsibilities: Build, train, and deploy ML models for tasks such as classification, regression, NLP, recommendation, or computer vision. Convert data science prototypes into production-ready applications . Design and implement ETL/data pipelines to support model training and inference. Optimize models and pipelines for performance, scalability, and efficiency . Collaborate with DevOps/MLOps teams to deploy and monitor models in production. Continuously evaluate and retrain models based on data and performance feedback. Maintain thorough documentation of models, features, and processes. Required Qualifications: 4+ years of hands-on experience in machine learning , data science , or AI engineering roles. Proficiency in Python and ML frameworks such as scikit-learn, TensorFlow, PyTorch , or similar. Solid understanding of ML algorithms , data preprocessing, model evaluation, and tuning. Experience working with cloud platforms (AWS/GCP) and containerization tools (e.g., Docker). Familiarity with SQL and NoSQL databases , and working with large-scale datasets. Strong problem-solving skills and a collaborative mindset. Good to Have: Experience with MLOps tools (e.g., MLflow, SageMaker, Kubeflow). Knowledge of deep learning , transformers , or LLMs . Familiarity with streaming data (Kafka, Spark Streaming) and real-time inference . Exposure to ElasticSearch for data indexing or log analytics. Interest in applied AI/ML innovation within domains like fin-tech, healthcare, or ecommerce. Education: Bachelor’s or Master’s degree in Computer Science, Data Science, AI/ML, or a related field.

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. Primary Responsibilities Develop and implement AI and machine learning strategies for healthcare domains Collaborate with cross-functional teams to identify and prioritize AI and machine learning initiatives Develop and run pipelines for data ingress and model output egress Develop and run scripts for ML model inference Design, implement, and maintain CI/CD pipelines for MLOps and DevOps functions Identify technical problems and develop software updates and fixes Develop scripts or tools to automate repetitive tasks Automate the provisioning and configuration of infrastructure resources Provide guidance on the best use of specific tools or technologies to achieve desired results Create documentation for infrastructure design and deployment procedures Utilize AI/ML frameworks and tools such as MLFlow, TensorFlow, PyTorch, Keras, Scikit-learn, etc. Lead and manage AI/ML teams and projects from ideation to delivery and evaluation Apply expertise in various AI/ML techniques, including deep learning, NLP, computer vision, recommender systems, reinforcement learning, and large language models Communicate complex AI/ML concepts and results to technical and non-technical audiences effectively 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 Required Qualifications Bachelor’s degree or higher in computer science engineering with a focus on language processing 8+ years of experience in Software Engineering, Data Science, or Analytics with 4+ years of experience in AI/ML engineering or related fields Experience in developing solutions in the NLP space and relevant projects Hands on Experience in AI and drive the development of innovative AI and machine learning solutions Experience with DevOps and CI/CD tools and practices, such as Git, Jenkins, Docker, Kubernetes, etc. Experience with Azure development environments Experience with using and deploying LLMs Knowledge of NLP literature, thrust areas, conference venues, and code repositories Familiarity with both open-source and OpenAI LLMs and RAG architecture Familiarity with UI tools like Streamlit, Flask, FAST APIs, Rest APIs, Docker containers Understanding of common NLP tasks such as text classification, entity recognition, entity extraction, and question answering. Proficient in Python and one of PySpark. Familiarity with python tools for data processing Proficiency in Python, R, or other programming languages for data analysis and AI/ML development Proven ability to develop and deploy data pipelines, machine learning models, or applications on cloud platforms (Azure, Databricks, AzureML) Proven excellent analytical and problem-solving skills, including the ability to disaggregate issues, identify root causes, and recommend solutions Proven hands-on skills with repository management and GPU use, and the ability to rapidly set up NLP pipelines for testing new ideas 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.

About Amgen Amgen harnesses the best of biology and technology to fight the world’s toughest diseases, and make people’s lives easier, fuller and longer. We discover, develop, manufacture and deliver innovative medicines to help millions of patients. Amgen helped establish the biotechnology industry more than 40 years ago and remains on the cutting-edge of innovation, using technology and human genetic data to push beyond what’s known today. About The Role Role Description: We are seeking a Sr Manager Data Sciences —Amgen’s most senior individual-contributor authority on building and scaling end-to-end machine-learning and generative-AI platforms. Sitting at the intersection of engineering excellence and data-science enablement, you will design the core services, infrastructure and governance controls that allow hundreds of practitioners to prototype, deploy and monitor models—classical ML, deep learning and LLMs—securely and cost-effectively. Acting as a “player-coach,” you will establish platform strategy, define technical standards, and partner with DevOps, Security, Compliance and Product teams to deliver a frictionless, enterprise-grade AI developer experience. Roles & Responsibilities: Develop and execute a multi-year data-science strategy and roadmap that directly supports corporate objectives, translating it into measurable quarterly OKRs for the team. Lead, mentor and grow a high-performing staff of data scientists and ML engineers, providing technical direction, career development, and continuous‐learning opportunities. Own the end-to-end delivery of advanced analytics and machine-learning solutions—from problem framing and data acquisition through model deployment, monitoring and iterative improvement—ensuring each project delivers clear business value. Prioritise and manage a balanced portfolio of initiatives, applying ROI, risk and resource-capacity criteria to allocate effort effectively across research, clinical, manufacturing and commercial domains. Provide hands-on guidance on algorithm selection and experimentation (regression, classification, clustering, time-series, deep learning, generative-AI, causal inference), ensuring methodological rigour and reproducibility. Establish and enforce best practices for code quality, version control, MLOps pipelines, model governance and responsible-AI safeguards (privacy, fairness, explainability). Partner with Data Engineering, Product, IT Security and Business stakeholders to integrate models into production systems via robust APIs, dashboards or workflow automations with well-defined SLAs. Manage cloud and on-prem analytics environments, optimising performance, reliability and cost; negotiate vendor contracts and influence platform roadmaps where appropriate. Champion a data-driven culture by communicating insights and model performance to VP/SVP-level leaders through clear storytelling, visualisations and actionable recommendations. Track emerging techniques, regulatory trends and tooling in AI/ML; pilot innovations that keep the organisation at the forefront of data-science practice and compliance requirements. Must-Have Skills: Leadership & Delivery: 10+ years in advanced analytics with 4+ years managing high-performing data-science or ML teams, steering projects from problem framing through production. Algorithmic Expertise: Deep command of classical ML, time-series, deep-learning (CNNs, transformers) and causal-inference techniques, with sound judgement on when and how to apply each. Production Engineering: Expert Python and strong SQL, plus hands-on experience deploying models via modern MLOps stacks (MLflow, Kubeflow, SageMaker, Vertex AI or Azure ML) with automated monitoring and retraining. Business Influence: Proven ability to translate complex analytics into concise, outcome-oriented narratives that inform VP/SVP-level decisions and secure investment. Cloud & Cost Governance: Working knowledge of AWS, Azure or GCP, including performance tuning and cost-optimisation for large-scale data and GPU/CPU workloads. Responsible AI & Compliance: Familiarity with privacy, security and AI-governance frameworks (GDPR, HIPAA, GxP, EU AI Act) and a track record embedding fairness, explainability and audit controls throughout the model lifecycle. Good-to-Have Skills: Experience in Biotechnology or pharma industry is a big plus Published thought-leadership or conference talks on enterprise GenAI adoption. Master’s degree in Computer Science and or Data Science Familiarity with Agile methodologies and Scaled Agile Framework (SAFe) for project delivery. Education and Professional Certifications Master’s degree with 10-14 + years of experience in Computer Science, IT or related field OR Bachelor’s degree with 12-17 + years of experience in Computer Science, IT or related field Certifications on GenAI/ML platforms (AWS AI, Azure AI Engineer, Google Cloud ML, etc.) are a plus. Soft Skills: Excellent analytical and troubleshooting skills. Strong verbal and written communication skills Ability to work effectively with global, virtual teams High degree of initiative and self-motivation. Ability to manage multiple priorities successfully. Team-oriented, with a focus on achieving team goals. Ability to learn quickly, be organized and detail oriented. Strong presentation and public speaking skills. EQUAL OPPORTUNITY STATEMENT Amgen is an Equal Opportunity employer and will consider you without regard to your race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status. We will ensure that individuals with disabilities are provided with reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request an accommodation.

Job Summary Job Title: Senior Software Development Engineer Artificial Intelligence & MLOps Location: Any Location Years of Experience: 4-6 Years Job Summary: We are seeking a highly skilled and experienced Senior Software Development Engineer specializing in Artificial Intelligence and MLOps. The ideal candidate will have a strong background in machine learning operations and software development, with a proven track record of deploying and managing machine learning models in production environments. This role requires a deep understanding of MLOps principles and practices, as well as the ability to collaborate effectively with cross functional teams to deliver high quality AI solutions. Responsibilities: Design, develop, and implement scalable machine learning models and algorithms. Manage the end to end lifecycle of machine learning models, including deployment, monitoring, and maintenance. Collaborate with data scientists, software engineers, and product managers to define and deliver AI solutions that meet business needs. Establish and maintain MLOps best practices, including version control, CI/CD pipelines, and automated testing. Optimize model performance and ensure reliability in production environments. Conduct code reviews and provide mentorship to junior team members. Stay updated with the latest trends and advancements in AI and MLOps technologies. Mandatory Skills: Strong expertise in MLOps practices and tools (e.g., MLflow, Kubeflow, TFX). Proficiency in programming languages such as Python, Java, or Scala. Experience with cloud platforms GCP is preferred (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes). Solid understanding of machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit learn). Experience with data engineering and ETL processes. Strong problem solving skills and ability to work in a fast paced environment. Preferred Skills: Familiarity with data visualization tools (e.g., Tableau, Power BI). Knowledge of big data technologies (e.g., Hadoop, Spark). Experience with Agile methodologies and project management tools. Understanding of DevOps practices and tools. Qualifications: Bachelor's or Master's degree in Computer Science, Engineering, or a related field. 7 10 years of experience in software development with a focus on AI and MLOps. Proven track record of successfully deploying machine learning models in production. Excellent communication and collaboration skills. If you are passionate about artificial intelligence and have a strong foundation in MLOps, we encourage you to apply and join our innovative team at TechM.

We are seeking individuals with advanced expertise in Machine Learning (ML) to join our dynamic team. As an Applied AI ML Lead within our Corporate Sector, you will play a pivotal role in developing machine learning and deep learning solutions, and experimenting with state of the art models. You will contribute to our innovative projects and drive the future of machine learning at AI Technologies. You will use your knowledge of ML tools and algorithms to deliver the right solution. You will be a part of an innovative team, working closely with our product owners, data engineers, and software engineers to build new AI/ML solutions and productionize them. You will also mentor other AI engineers and scientists while fostering a culture of continuous learning and technical excellence. We are looking for someone with a passion for data, ML, and programming, who can build ML solutions at-scale with a hands-on approach with detailed technical acumen. Job responsibilities Serve as a subject matter expert on a wide range of machine learning techniques and optimizations. Provide in-depth knowledge of machine learning algorithms, frameworks, and techniques. Enhance machine learning workflows through advanced proficiency in large language models (LLMs) and related techniques. Conduct experiments using the latest machine learning technologies, analyze results, and tune models. Engage in hands-on coding to transition experimental results into production solutions by collaborating with the engineering team, owning end-to-end code development in Python for both proof of concept/experimentation and production-ready solutions. Optimize system accuracy and performance by identifying and resolving inefficiencies and bottlenecks, collaborating with product and engineering teams to deliver tailored, science and technology-driven solutions. Integrate Generative AI within the machine learning platform using state-of-the-art techniques, driving decisions that influence product design, application functionality, and technical operations and processes Required qualifications, capabilities, and skills Formal training or certification on AI/ML concepts and 5+ years applied experience Hans on experience in programming languages, particularly Python. Manage to apply data science and machine learning techniques to address business challenges. Strong background in Natural Language Processing (NLP) and Large Language Models (LLMs). Expertise in deep learning frameworks such as PyTorch or TensorFlow, and advanced applied ML areas like GPU optimization, finetuning, embedding models, inferencing, prompt engineering, evaluation, and RAG (Similarity Search). Manage to complete tasks and projects independently with minimal supervision, with a passion for detail and follow-through. Excellent communication skills, team player, and demonstrated leadership in collaborating effectively with engineers, product managers, and other ML practitioners Preferred qualifications, capabilities, and skills Exposure with Ray, MLFlow, and/or other distributed training frameworks. MS and/or PhD in Computer Science, Machine Learning, or a related field. Understanding of Search/Ranking, Recommender systems, Graph techniques, and other advanced methodologies. Familiar in Reinforcement Learning or Meta Learning. Understanding of Large Language Model (LLM) techniques, including Agents, Planning, Reasoning, and other related methods. Exposure building and deploying ML models on cloud platforms such as AWS and AWS tools like Sagemaker, EKS, etc.

About the Role We are seeking a visionary and hands-on AI Lead to architect, build, and scale next-generation Generative and Agentic AI systems. In this role, you will drive the end-to-end lifecycle—from research and prototyping to production deployment—guiding a team of AI engineers and collaborating cross-functionally to deliver secure, scalable, and impactful AI solutions across multimodal and LLM-based ecosystems. Key Responsibilities Architect and oversee the development of GenAI and Agentic AI workflows, including multi-agent systems and LLM-based pipelines. Guide AI engineers in best practices for RAG (Retrieval-Augmented Generation), prompt engineering, and agent design. Evaluate and implement the right technology stack: open source (Hugging Face, LangChain, LlamaIndex) vs. closed source (OpenAI, Anthropic, Mistral). Lead fine-tuning and adapter-based training (e.g., LoRA, QLoRA, PEFT). Drive inference optimization using quantization, ONNX, TensorRT, and related tools. Build and refine RAG pipelines using embedding models, vector DBs (FAISS, Qdrant), chunking strategies, and hybrid knowledge graph systems. Manage LLMOps with tools like Weights & Biases, MLflow, and ClearML, ensuring experiment reproducibility and model versioning. Design and implement evaluation frameworks for truthfulness, helpfulness, toxicity, and hallucinations. Integrate guardrails, content filtering, and data privacy best practices into GenAI systems. Lead development of multi-modal AI systems (VLMs, CLIP, LLaVA, video-text fusion models). Oversee synthetic data generation for fine-tuning in low-resource domains. Design APIs and services for Model-as-a-Service (MaaS) and AI agent orchestration. Collaborate with product, cloud, and infrastructure teams to align on deployment, GPU scaling, and cost optimization. Translate cutting-edge AI research into usable product capabilities, from prototyping to production. Mentor and grow the AI team, establishing R&D best practices and benchmarks. Stay up-to-date with emerging trends (arXiv, Papers With Code) to keep the organization ahead of the curve. Required Skills & Expertise AI & ML Foundations: Generative AI, LLMs, Diffusion Models, Agentic AI Systems, Multi-Agent Planning, Prompt Engineering, Feedback Loops, Task Decomposition Ecosystem & Frameworks: Hugging Face, LangChain, OpenAI, Anthropic, Mistral, LLaMA, GPT, Claude, Mixtral, Falcon, etc. Fine-tuning & Inference: LoRA, QLoRA, PEFT, ONNX, TensorRT, DeepSpeed, vLLM Data & Retrieval Systems: FAISS, Qdrant, Chroma, Pinecone, Hybrid RAG + Knowledge Graphs MLOps & Evaluation: Weights & Biases, ClearML, MLflow, Evaluation metrics (truthfulness, helpfulness, hallucination) Security & Governance: Content moderation, data privacy, model alignment, ethical constraints Deployment & Ops: Cloud (AWS, GCP, Azure) with GPU scaling, Serverless LLMs, API-based inference, Docker/Kubernetes Other: Multi-modal AI (images, video, audio), API Design (Swagger/OpenAPI), Research translation and POC delivery Preferred Qualifications 7+ years in AI/ML roles, with at least 2–3 years in a technical leadership capacity Proven experience deploying LLM-powered systems at scale Experience working with cross-functional product and infrastructure teams Contributions to open-source AI projects or published research papers (a plus) Strong communication skills to articulate complex AI concepts to diverse stakeholders Why Join Us? Work at the forefront of AI innovation with opportunities to publish, build, and scale impactful systems Lead a passionate team of engineers and researchers Shape the future of ethical, explainable, and usable AI products Ready to shape the next wave of AI? Apply now and join us on this journey! Job Type: Full-time Pay: ₹2,000,000.01 - ₹3,002,234.14 per year Benefits: Flexible schedule Health insurance Paid time off Provident Fund Schedule: Day shift Monday to Friday Supplemental Pay: Yearly bonus Work Location: In person

We are united in our mission to make a positive impact on healthcare. Join Us! South Florida Business Journal, Best Places to Work 2024 Inc. 5000 Fastest-Growing Private Companies in America 2024 2024 Black Book Awards, ranked #1 EHR in 11 Specialties 2024 Spring Digital Health Awards, "Web-based Digital Health" category for EMA Health Records (Gold) 2024 Stevie American Business Award (Silver), New Product and Service: Health Technology Solution (Klara) Who we are: We Are Modernizing Medicine (WAMM)! We're a team of bright, passionate, and positive problem-solvers on a mission to place doctors and patients at the center of care through an intelligent, specialty-specific cloud platform. Our vision is a world where the software we build increases medical practice success and improves patient outcomes. Founded in 2010 by Daniel Cane and Dr. Michael Sherling, we have grown to over 3400 combined direct and contingent team members serving eleven specialties, and we are just getting started! ModMed's global headquarters is based in Boca Raton, FL, with a growing office in Hyderabad, India, and a robust remote workforce across the US, Chile, and Germany. ModMed is hiring a driven ML Ops Engineer 2 to join our positive, passionate, and high-performing team focused on scalable ML Systems. This is an exciting opportunity to You as you will collaborate with data scientists, engineers, and other cross-functional teams to ensure seamless model deployment, monitoring, and automation. If you're passionate about cloud infrastructure, automation, and optimizing ML pipelines, this is the role for you within a fast-paced Healthcare IT company that is truly Modernizing Medicine! Key Responsibilities: Model Deployment & Automation: Develop, deploy, and manage ML models on Databricks using MLflow for tracking experiments, managing models, and registering them in a centralized repository. Infrastructure & Environment Management: Set up scalable and fault-tolerant infrastructure to support model training and inference in cloud environments such as AWS, GCP, or Azure. Monitoring & Performance Optimization: Implement monitoring systems to track model performance, accuracy, and drift over time. Create automated systems for re-training and continuous learning to maintain optimal performance. Data Pipeline Integration: Collaborate with the data engineering team to integrate model pipelines with real-time and batch data processing frameworks, ensuring seamless data flow for training and inference. Skillset & Qualification Model Deployment: Experience with deploying models in production using cloud platforms like AWS Sagemaker, GCP AI Platform, or Azure ML Studio. Version Control & Automation: Experience with MLOps tools such as MLflow, Kubeflow, or Airflow to automate and monitor the lifecycle of machine learning models. Cloud Expertise: Experience with cloud-based machine learning services on AWS, Google Cloud, or Azure, ensuring that models are scalable and efficient. Engineers must be skilled in measuring and optimizing model performance through metrics like AUC, precision, recall, and F1-score, ensuring that models are robust and reliable in production settings. Education: Bachelor's or Master's degree in Data Science, Statistics, Mathematics, or a related technical field. ModMed in India Benefit Highlights: High growth, collaborative, transparent, fun, and award-winning culture Comprehensive benefits package including medical for you, your family, and your dependent parents The company supported community engagement opportunities along with a paid Voluntary Time Off day to use for volunteering in your community of interest Global presence, and in-person collaboration opportunities; dog-friendly HQ (US), Hybrid office-based roles and remote availability Company-sponsored Employee Resource Groups that provide engaged and supportive communities within ModMed ModMed Benefits Highlight: At ModMed, we believe it's important to offer a competitive benefits package designed to meet the diverse needs of our growing workforce. Eligible Modernizers can enroll in a wide range of benefits: India Meals & Snacks: Enjoy complimentary office lunches & dinners on select days and healthy snacks delivered to your desk, Insurance Coverage: Comprehensive health, accidental, and life insurance plans, including coverage for family members, all at no cost to employees, Allowances: Annual wellness allowance to support your well-being and productivity, Earned, casual, and sick leaves to maintain a healthy work-life balance, Bereavement leave for difficult times and extended medical leave options, Paid parental leaves, including maternity, paternity, adoption, surrogacy, and abortion leave, Celebration leave to make your special day even more memorable, and company-paid holidays to recharge and unwind. United States Comprehensive medical, dental, and vision benefits, including a company Health Savings Account contribution, 401(k): ModMed provides a matching contribution each payday of 50% of your contribution deferred on up to 6% of your compensation. After one year of employment with ModMed, 100% of any matching contribution you receive is yours to keep. Generous Paid Time Off and Paid Parental Leave programs, Company paid Life and Disability benefits, Flexible Spending Account, and Employee Assistance Programs, Company-sponsored Business Resource & Special Interest Groups that provide engaged and supportive communities within ModMed, Professional development opportunities, including tuition reimbursement programs and unlimited access to LinkedIn Learning, Global presence and in-person collaboration opportunities; dog-friendly HQ (US), Hybrid office-based roles and remote availability for some roles, Weekly catered breakfast and lunch, treadmill workstations, Zen, and wellness rooms within our BRIC headquarters. PHISHING SCAM WARNING: ModMed is among several companies recently made aware of a phishing scam involving imposters posing as hiring managers recruiting via email, text and social media. The imposters are creating misleading email accounts, conducting remote "interviews," and making fake job offers in order to collect personal and financial information from unsuspecting individuals. Please be aware that no job offers will be made from ModMed without a formal interview process, and valid communications from our hiring team will come from our employees with a ModMed email address (first.lastname@modmed.com). Please check senders' email addresses carefully. Additionally, ModMed will not ask you to purchase equipment or supplies as part of your onboarding process. If you are receiving communications as described above, please report them to the FTC website.

Gurgaon, India R&D 48747 Regular No Full Time (F) <10% India Job Description Overview Keysight is on the forefront of technology innovation, delivering breakthroughs and trusted insights in electronic design, simulation, prototyping, test, manufacturing, and optimization. Our ~15,000 employees create world-class solutions in communications, 5G, automotive, energy, quantum, aerospace, defense, and semiconductor markets for customers in over 100 countries. Learn more about what we do. We are seeking a passionate and skilled AI Engineer with 0-2 years of exerience to join our R&D team, focusing on the design, development, and deployment of intelligent chatbot systems and robust data engineering pipelines. This role bridges conversational AI and data infrastructure, enabling scalable, intelligent digital assistants that enhance user experience and operational efficiency. Our award-winning culture embraces a bold vision of where technology can take us and a passion for tackling challenging problems with industry-first solutions. We believe that when people feel a sense of belonging, they can be more creative, innovative, and thrive at all points in their careers. Responsibilities Key Responsibilities Chatbot Design & Development Design, develop, and deploy AI-powered chatbots using NLP and LLM frameworks (e.g., Open Source, Rasa, Dialogflow, OpenAI, Azure Bot Framework). Collaborate with UX and product teams to define conversational flows and user intents. Continuously improve chatbot performance through user feedback, analytics, and retraining cycles. Ensure chatbot compliance with data privacy and governance standards. Data Engineering Build and maintain scalable data pipelines to support chatbot training and analytics. Integrate structured and unstructured data from multiple sources (e.g., APIs, databases, logs). Implement data preprocessing, transformation, and storage strategies optimized for AI/ML workloads. Collaborate with data scientists to ensure data readiness for model training and evaluation. Qualifications Required Qualifications Bachelor’s or Master’s degree in Computer Science, Data Engineering, AI/ML, or related field. 0-2 years of experience in AI/ML engineering or data engineering roles. Proficiency in Python and familiarity with Java or Scala. Strong software development and collaboration skills. Experience with NLP libraries (e.g., spaCy, Hugging Face Transformers) and chatbot platforms. Hands-on experience with data pipeline tools (e.g., Apache Airflow, Spark, Kafka). Familiarity with cloud platforms (AWS, Azure, or GCP) and containerization (Docker, Kubernetes). Strong understanding of data modeling, ETL processes, and data governance. Preferred Skills Exposure to MLOps practices and tools (e.g., MLflow, Kubeflow). Experience with LLM fine-tuning and prompt engineering. Knowledge of RESTful APIs and microservices architecture. Familiarity with analytics dashboards and chatbot performance metrics. Careers Privacy Statement***Keysight is an Equal Opportunity Employer.***

Overview Keysight is on the forefront of technology innovation, delivering breakthroughs and trusted insights in electronic design, simulation, prototyping, test, manufacturing, and optimization. Our ~15,000 employees create world-class solutions in communications, 5G, automotive, energy, quantum, aerospace, defense, and semiconductor markets for customers in over 100 countries. Learn more about what we do. We are seeking a passionate and skilled AI Engineer with 0-2 years of exerience to join our R&D team, focusing on the design, development, and deployment of intelligent chatbot systems and robust data engineering pipelines. This role bridges conversational AI and data infrastructure, enabling scalable, intelligent digital assistants that enhance user experience and operational efficiency. Our award-winning culture embraces a bold vision of where technology can take us and a passion for tackling challenging problems with industry-first solutions. We believe that when people feel a sense of belonging, they can be more creative, innovative, and thrive at all points in their careers. Responsibilities Key Responsibilities Chatbot Design & Development Design, develop, and deploy AI-powered chatbots using NLP and LLM frameworks (e.g., Open Source, Rasa, Dialogflow, OpenAI, Azure Bot Framework). Collaborate with UX and product teams to define conversational flows and user intents. Continuously improve chatbot performance through user feedback, analytics, and retraining cycles. Ensure chatbot compliance with data privacy and governance standards. Data Engineering Build and maintain scalable data pipelines to support chatbot training and analytics. Integrate structured and unstructured data from multiple sources (e.g., APIs, databases, logs). Implement data preprocessing, transformation, and storage strategies optimized for AI/ML workloads. Collaborate with data scientists to ensure data readiness for model training and evaluation. Qualifications Required Qualifications Bachelor’s or Master’s degree in Computer Science, Data Engineering, AI/ML, or related field. 0-2 years of experience in AI/ML engineering or data engineering roles. Proficiency in Python and familiarity with Java or Scala. Strong software development and collaboration skills. Experience with NLP libraries (e.g., spaCy, Hugging Face Transformers) and chatbot platforms. Hands-on experience with data pipeline tools (e.g., Apache Airflow, Spark, Kafka). Familiarity with cloud platforms (AWS, Azure, or GCP) and containerization (Docker, Kubernetes). Strong understanding of data modeling, ETL processes, and data governance. Preferred Skills Exposure to MLOps practices and tools (e.g., MLflow, Kubeflow). Experience with LLM fine-tuning and prompt engineering. Knowledge of RESTful APIs and microservices architecture. Familiarity with analytics dashboards and chatbot performance metrics. Careers Privacy Statement***Keysight is an Equal Opportunity Employer.***

At Prodigal, we’re reshaping the future of consumer finance. Founded in 2018 by IITB alumni, our journey began with one bold mission: to eradicate the inefficiencies and confusion that have plagued the lending and collections industry for decades. Today, we stand at the forefront of a seismic shift in the industry, pioneering the concept of consumer finance intelligence. Powered by our cutting-edge platform, Prodigal’s Intelligence Engine, we’re creating the next-generation agentic workforce for consumer finance—one that empowers companies to achieve unprecedented levels of operational excellence. With over half a billion consumer finance interactions processed and a growing impact on more than 100 leading companies across North America, we’ve established ourselves as the go-to partner for organizations that demand more from their AI solutions. Our unparalleled experience, coupled with our trusted customer relationships, uniquely positions us to build generative AI solutions that will revolutionize the future of consumer finance. At Prodigal, we are driven by a singular, unrelenting purpose: to transform how consumer finance companies engage with their customers and, in turn, drive successful outcomes for all. About The Role We're seeking an exceptional Agent Engineer specializing in Applied AI and Prompt Engineering to join our team building next-generation industry centric vertical Voice AI Agents. In this role, you'll be at the intersection of AI engineering and customer experience, crafting and optimizing prompts that power natural, effective voice conversations in consumer finance. You'll work directly with our proprietary voice AI technology, analyzing conversation data, iterating on prompt strategies, and implementing systematic approaches to improve agent performance. This is a hands-on technical role that requires both engineering excellence and a deep understanding of conversational AI design. 🏆 Key Responsibilities Prompt Engineering & Optimization Design, test, and refine prompts for voice AI agents handling complex financial conversations Develop systematic prompt engineering methodologies and best practices for voice interactions Ability to meta-prompt and run experiments with different LLMs, bringing in m Bring in new agent architectures to bring in the lowest latencies possible while maintaining high accuracy Create prompt templates and frameworks that scale across different use cases and customer segments Implement A/B testing strategies to measure and improve prompt effectiveness Data-Driven Optimization Analyze conversation transcripts and performance metrics to identify improvement opportunities Use our Simulation Platform and existing call corpus of our customers to tune and improve AI Agent performance Develop automated evaluation frameworks for AI agent quality assessment Create feedback loops (semi or fully automated) between production data and prompt refinements Optimize prompts for latency, accuracy, and natural conversation flow Voice AI Development Collaborate with ML engineers to improve voice recognition and synthesis quality Design conversation flows that handle edge cases and error recovery gracefully Implement context management strategies for multi-turn conversations Develop domain-specific language models for financial services Customer Success & Travel Travel to customer sites to learn from human agents and gather requirements Conduct on-site prompt optimization based on customer-specific needs to deliver rapid iterations of prototype versions ✅ Requirements Must-Have Qualifications B.E/B.Tech/M.Tech in Computer Science, AI/ML, Linguistics, or equivalent Strong Python programming skills and experience with ML frameworks Ability to work with large-scale conversation data Excellent analytical and problem-solving skills Strong verbal and written communication skills and ability to explain technical concepts clearly Willingness to travel in the US for customer engagements Technical Skills Proficiency in prompt engineering techniques (few-shot learning, chain-of-thought meta-prompting, etc.) Knowledge of SQL and data analysis tools (Pandas, NumPy) Experience with experiment tracking and MLOps tools Understanding of real-time system constraints and latency optimization Bonus Qualifications Familiarity with voice biometrics and authentication Experience with real-time streaming architectures Published research or blog posts on prompt engineering or conversational AI Experience with multilingual voice AI systems 🎁 What We Offer Job Benefits GenAI Experience – Work at the cutting edge of voice AI and prompt engineering, shaping the future of conversational AI in consumer finance World-class Team – Learn from and collaborate with experts from BCG, Deloitte, Meta, Amazon, and top institutes like IIT and IIM Continuous Education – Full sponsorship for courses, certifications, conferences, and learning materials related to AI and prompt engineering Travel Opportunities – Gain exposure to diverse customer environments and real-world AI implementations Health Insurance – Comprehensive coverage for you and your family Flexible Schedule – Work when you're most productive, with core collaboration hours Generous Leave Policy – Unlimited PTO to ensure you stay refreshed and creative Food at Office – All meals provided when working from office Recreation & Team Activities – Regular team bonding through sports, games, and social events Our Tech Stack AI/ML: GPT, Claude, Gemini, Custom LLMs Languages: Python Infrastructure: AWS (Lambda, SageMaker, EKS), LiveKit for Real-time streaming Data: MongoDB, PostgreSQL, Databricks, Redis Tools: MLflow, Custom prompt management platforms Why This Role Matters As a Founding Agent Engineer Focused On Voice AI And Prompt Engineering, You'll Directly Impact How Millions Of Consumers Interact With Financial Services Companies, And Also Be Able To Lay Out How Agent Engineering Grows At Prodigal. Your Work Will Have Immense Implications For Consumer Finance How Prodigal operates Setting the industry standard in Voice AI From day 1, Prodigal has been defined by talented, humble, and hungry leaders and we want this mindset and culture to continue to blossom from top to bottom in the company. If you have an entrepreneurial spirit and want to work in a fast-paced, intellectually-stimulating environment where you will be pushed to grow, then please reach out because we are looking to build a transformational company that reinvents one of the biggest industries in the US. To learn more about us - please visit the following: Our Story - https://www.prodigaltech.com/our-story What shapes our thinking - https://link.prodigaltech.com/our-thesis Our website - https://www.prodigaltech.com/

Job Title: Lead AI/ML Engineer / Data Scientist (GIS & Image Processing) Location: Pune Experience: 4+ Years Employment Type: Full-Time Highly motivated and experienced Lead AI/ML Engineer or Data Scientist with deep expertise in GIS and/or Image Processing to architect and drive our AI initiatives. You will lead a team of engineers and data scientists, define technical direction, and deliver scalable, production-grade solutions for image and geospatial intelligence applications. Key Responsibilities: Lead the design, development, and deployment of AI/ML models for image and geospatial data processing. Architect end-to-end pipelines, from data ingestion and preprocessing to model deployment and monitoring. Work hands-on with geospatial datasets (satellite imagery, drone data, maps) and apply advanced image processing and computer vision techniques. Guide and mentor a team of junior and mid-level engineers/data scientists. Collaborate with product managers, domain experts, and stakeholders to align technical solutions with business goals. Review and improve model performance, scalability, and robustness through continuous evaluation and tuning. Ensure best practices in coding, model management, MLOps, and documentation. Stay up to date with the latest trends in AI, GIS, and image analytics, and bring innovative ideas into the team. Required Qualifications: Bachelor’s or Master’s degree in Computer Science, Geoinformatics or related fields. PhD is a plus. 6+ years of experience in AI/ML or Data Science roles with a strong focus on image processing or GIS. Proficient in Python, ML/DL frameworks (TensorFlow, PyTorch), and image processing libraries (OpenCV, scikit-image, PIL). Hands-on experience with geospatial tools and libraries (QGIS, GDAL, Geopandas, ArcGIS, rasterio). Proven track record in leading AI/ML projects and delivering production-grade systems. Experience with cloud infrastructure (AWS, GCP, or Azure) and containerized deployments (Docker, Kubernetes). Strong understanding of geospatial data formats, coordinate systems, and remote sensing concepts. Preferred Skills : Experience with deep learning models for segmentation (e.g., UNet, Mask R-CNN) or object detection (YOLO, Faster R-CNN). Knowledge of satellite/drone data sources and preprocessing workflows. Familiarity with MLOps practices and tools like MLflow, Airflow, or Kubeflow. Exposure to data privacy, ethical AI, and regulatory compliance in geospatial applications. Job Types: Full-time, Permanent Pay: ₹1,000,000.00 - ₹1,400,000.00 per year Benefits: Health insurance Provident Fund Schedule: Day shift Experience: AI/ML: 6 years (Preferred) Work Location: In person

We're Hiring! Machine Learning Engineer for a B2B SaaS based startup in Noida. 🔹 Position: Machine Learning Engineer 🔹 Experience: 3.5 Years to 5 Years 🔹 Location: Noida, Sector 90 🔹 Work Mode: 5 Days | Work From Office 🔹 Notice Period: Immediate to 30 Days Key Responsibilities Design, develop, and optimize machine learning models for various business applications. Build and maintain scalable AI feature pipelines for efficient data processing and model training. Develop robust data ingestion, transformation, and storage solutions for big data. Implement and optimize ML workflows, ensuring scalability and efficiency. Monitor and maintain deployed models, ensuring performance, reliability, and retraining when necessary. Qualifications and Experience Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field. 3.5+ years of experience in machine learning, deep learning, or data science roles. Proficiency in Python and ML frameworks/tools such as PyTorch, Langchain Experience with data processing frameworks like Spark, Dask, Airflow, and Dagster Hands-on experience with cloud platforms (AWS, GCP, Azure) and ML services. Experience with MLOps tools like MLflow, Kubeflow Familiarity with containerisation and orchestration tools like Docker and Kubernetes. Excellent problem-solving skills and ability to work in a fast-paced environment. Strong communication and collaboration skills. If you’re ready to take on a leadership role and thrive in a dynamic startup environment, share your profile at gautam@mounttalent.com.

This role is for one of Weekday's clients Min Experience: 0 years Location: Bengaluru JobType: full-time Requirements About the Role: We are seeking a motivated and passionate Machine Learning Engineer to join our growing AI/ML team. This is an excellent opportunity for recent graduates or early-career professionals to work on real-world applications of Machine Learning (ML) , Artificial Intelligence (AI) , and Natural Language Processing (NLP) technologies. You'll be part of a team that builds intelligent systems to solve complex problems and deliver value to our customers across domains. If you're a self-starter who's eager to apply theoretical knowledge into practice, experiment with state-of-the-art tools like TensorFlow , and work collaboratively on challenging problems in NLP and AI, this role is for you. Key Responsibilities: Assist in the development, training, and evaluation of machine learning models using Python and libraries such as TensorFlow and Scikit-learn. Support data collection, preprocessing, and transformation tasks to build robust ML pipelines. Collaborate with data scientists, software engineers, and product teams to understand problem requirements and deliver ML-based solutions. Work on natural language processing tasks such as text classification, sentiment analysis, named entity recognition, and language modeling. Implement ML models into production environments and monitor model performance. Conduct research and stay updated with the latest developments in AI/ML and NLP. Optimize and tune models for accuracy, speed, and scalability. Prepare documentation, reports, and presentations to communicate results and findings to stakeholders. Required Skills: Basic understanding of machine learning concepts such as supervised/unsupervised learning, classification, regression, and clustering. Familiarity with Python programming and common ML libraries like TensorFlow, Keras, Scikit-learn, and Pandas. Exposure to natural language processing (NLP) tasks and basic algorithms. Understanding of data preprocessing, feature engineering, and model evaluation techniques. Enthusiasm to learn and work with deep learning models and frameworks. Strong analytical thinking and problem-solving skills. Good communication skills and the ability to work in a collaborative environment. Nice to Have: Internship or project experience in ML, AI, or NLP. Knowledge of neural networks, RNNs, CNNs, or transformer models like BERT or GPT. Experience working with large datasets or on cloud platforms such as AWS, GCP, or Azure. Understanding of version control (Git) and deployment tools (Docker, MLflow, etc.). Participation in ML competitions (e.g., Kaggle) or open-source contributions. Educational Qualification: Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Statistics, or a related field.

Job Title: Devops Engineer with MlOps & LLM ( Remote ) Job Type: Contract Contract Duration: 2 Months (as needed basis) Experience: 6+ Years Location: Remote Job Description & Responsibilities We Are Seeking a skilled and proactive DevOps Engineer to support with expertise to contribute to the design and development of a scalable, user-friendly front-end application for our AI-driven platform enabling search, recommendations and GIS based interactions.. The ideal candidate will have extensive experience in managing both cloud and on-premises infrastructure, implementing CI/CD pipelines, and optimizing system performance to ensure seamless integration and deployment of features. They should possess deep expertise in observability tooling, container orchestration, and MLOps for large language models (LLMs). This role involves managing the full DevOps lifecycle while closely collaborating with development, QA, and operations teams to drive reliability, scalability, and continuous delivery across secure, distributed environments. Manage infrastructure across AWS/Azure for development and lower environments. Setup, configure, and manage Kubernetes (K8s) clusters in hybrid environments. Integrate OpenTelemetry and Application Performance Monitoring (APM) tools for observability and performance tracking. Collaborate with ML teams to implement and scale MLOps pipelines for training, tuning, and deploying LLMs Build and maintain continuous integration/continuous deployment (CI/CD) pipelines for efficient software delivery. Automate build, test, and deployment processes to streamline development workflows. Manage and configure development, staging, and production environments. Ensure consistency and stability across all environments through automation and configuration management tools. Implement security best practices, including access controls, vulnerability scanning, and compliance monitoring. Regularly update and patch infrastructure components to mitigate security risks. Set up and maintain monitoring tools to track application performance and system health. Configure logging and alerting mechanisms to proactively identify and address issues. Work closely with development, QA, and operations teams to troubleshoot issues and ensure smooth deployments. Provide guidance and support for infrastructure-related tasks and challenges. Identify and implement improvements to DevOps processes and workflows. Stay updated on industry trends and tools to enhance DevOps practices. Primary Skills Bachelor's degree in Computer Science, Information Technology, or a related field. 3–5 years of experience as a DevOps Engineer or in a similar role. Proficiency in designing and managing CI/CD pipelines using Azure DevOps, Jenkins, or similar tools. Experience with tools like Kubeflow, MLflow, or SageMaker for MLOps. Secondary Skills(if Any) Proficiency in containerization tools such as Docker and orchestration platforms like Kubernetes. Strong knowledge of version control systems like Git and branching strategies. Understanding of network configurations, VPNs, firewalls, and load balancers. Familiarity with Agile methodologies and DevOps principles. Certifications Required(if Any) Certification in relevant skills will be considered an added advantage

Overview Keysight is on the forefront of technology innovation, delivering breakthroughs and trusted insights in electronic design, simulation, prototyping, test, manufacturing, and optimization. Our ~15,000 employees create world-class solutions in communications, 5G, automotive, energy, quantum, aerospace, defense, and semiconductor markets for customers in over 100 countries. Learn more about what we do. We are seeking a passionate and skilled AI Engineer with 0-2 years of exerience to join our R&D team, focusing on the design, development, and deployment of intelligent chatbot systems and robust data engineering pipelines. This role bridges conversational AI and data infrastructure, enabling scalable, intelligent digital assistants that enhance user experience and operational efficiency. Our award-winning culture embraces a bold vision of where technology can take us and a passion for tackling challenging problems with industry-first solutions. We believe that when people feel a sense of belonging, they can be more creative, innovative, and thrive at all points in their careers. Responsibilities Key Responsibilities Chatbot Design & Development Design, develop, and deploy AI-powered chatbots using NLP and LLM frameworks (e.g., Open Source, Rasa, Dialogflow, OpenAI, Azure Bot Framework). Collaborate with UX and product teams to define conversational flows and user intents. Continuously improve chatbot performance through user feedback, analytics, and retraining cycles. Ensure chatbot compliance with data privacy and governance standards. Data Engineering Build and maintain scalable data pipelines to support chatbot training and analytics. Integrate structured and unstructured data from multiple sources (e.g., APIs, databases, logs). Implement data preprocessing, transformation, and storage strategies optimized for AI/ML workloads. Collaborate with data scientists to ensure data readiness for model training and evaluation. Qualifications Required Qualifications Bachelor’s or Master’s degree in Computer Science, Data Engineering, AI/ML, or related field. 0-2 years of experience in AI/ML engineering or data engineering roles. Proficiency in Python and familiarity with Java or Scala. Strong software development and collaboration skills. Experience with NLP libraries (e.g., spaCy, Hugging Face Transformers) and chatbot platforms. Hands-on experience with data pipeline tools (e.g., Apache Airflow, Spark, Kafka). Familiarity with cloud platforms (AWS, Azure, or GCP) and containerization (Docker, Kubernetes). Strong understanding of data modeling, ETL processes, and data governance. Preferred Skills Exposure to MLOps practices and tools (e.g., MLflow, Kubeflow). Experience with LLM fine-tuning and prompt engineering. Knowledge of RESTful APIs and microservices architecture. Familiarity with analytics dashboards and chatbot performance metrics. Careers Privacy Statement***Keysight is an Equal Opportunity Employer.***

About Company : GSPANN is a global IT services and consultancy provider headquartered in Milpitas, California (U.S.A.). With five global delivery centers across the globe, GSPANN provides digital solutions that support the customer buying journeys of B2B and B2C brands worldwide. With a strong focus on innovation and client satisfaction, GSPANN delivers cutting-edge solutions that drive business success and operational excellence. GSPANN helps retail, finance, manufacturing, and high-technology brands deliver competitive customer experiences and increased revenues through our solution delivery, technologies, practices, and operations for each client. For more information, visit www.gspann.com Job Position (Title):AI Ops + ML Ops Engineer Experience Required:4+ Years Job Type: Fulltime Number of positions: 3 (1 Senior and 2 Junior) Location: Hyderabad/Pune/Gurugram Technical Skill Requirements Mandatory Skills - ML Ops, Devops, Python, Cloud, AI Ops Role and Responsibilities Strategic & Leadership: Architect and lead the implementation of scalable AIOps and MLOps frameworks. Mentor junior engineers and data scientists on best practices in model deployment and operational excellence. Collaborate with product managers, SREs, and business stakeholders to align technical strategies with organizational goals. Define and enforce engineering standards, SLAs, SLIs, and SLOs for ML and AIOps services. MLOps Focus: Design and manage ML CI/CD pipelines for training, testing, deployment, and monitoring using tools like Kubeflow, MLflow, or Airflow . Implement advanced monitoring for model performance (drift, latency, accuracy) and automate retraining workflows. Lead initiatives on model governance, reproducibility, traceability, and compliance (e.g., FAIR, audit logging). AIOps Focus: Develop AI/ML-based solutions for proactive infrastructure monitoring, predictive alerting, and intelligent incident management. Integrate and optimize observability tools ( Prometheus, Grafana, ELK, Dynatrace, Splunk, Datadog ) for anomaly detection and root cause analysis. Automate incident response workflows using playbooks, runbooks, and self-healing mechanisms. Use statistical methods and ML to analyze logs, metrics, and traces at scale. Required Skills 4+ years of experience in DevOps, MLOps, or AIOps, with at least 2+ years in a leadership or senior engineering role. Expert-level proficiency in Python , Bash , and familiarity with Go or Java . Deep experience with containerization (Docker) , orchestration (Kubernetes) , and cloud platforms (AWS, GCP, Azure) . Proficient with CI/CD tools and infrastructure-as-code ( Terraform, Ansible, Helm ). Strong understanding of ML lifecycle management, model monitoring, and data pipeline orchestration. Experience deploying and maintaining large-scale observability and telemetry systems. Preferred Qualifications: Experience with streaming data platforms: Kafka, Spark, Flink . Hands-on experience with Service Mesh (Istio/Linkerd) for traffic and security management. Familiarity with data security, privacy, and compliance standards (e.g., GDPR, HIPAA). Certifications in AWS/GCP DevOps, Kubernetes, or MLOps are a strong plus. Why choose GSPANN At GSPANN, we don’t just serve our clients—we co-create. The GSPANNians are passionate technologists who thrive on solving the toughest business challenges, delivering trailblazing innovations for marquee clients. This collaborative spirit fuels a culture where every individual is encouraged to sharpen their skills, feed their curiosity, and take ownership to learn, experiment, and succeed. We believe in celebrating each other’s successes—big or small—and giving back to the communities we call home. If you’re ready to push boundaries and be part of a close-knit team that’s shaping the future of tech, we invite you to carry forward the baton of innovation with us. Let’s Co-Create the Future—Together. Discover Your Inner Technologist Explore and expand the boundaries of tech innovation without the fear of failure. Accelerate Your Learning Shape your career while scripting the future of tech. Seize the ample learning opportunities to grow at a rapid pace. Feel Included At GSPANN, everyone is welcome. Age, gender, culture, and nationality do not matter here, what matters is YOU. Inspire and Be Inspired When you work with the experts, you raise your game. At GSPANN, you’re in the company of marquee clients and extremely talented colleagues. Enjoy Life We love to celebrate milestones and victories, big or small. Ever so often, we come together as one large GSPANN family. Give Back Together, we serve communities. We take steps, small and large so we can do good for the environment, weaving in sustainability and social change in our endeavors. We invite you to carry forward the baton of innovation in technology with us. Let’s Co-Create

Job Title: Machine Learning Lead Engineer Job Summary: We are looking for a highly skilled Machine Learning Lead Engineer to lead the development and deployment of production-grade ML solutions. You will be responsible for overseeing the engineering efforts of the ML team, ensuring scalable model development, robust data pipelines, and seamless integration with production systems. This is a key technical leadership role for someone passionate about driving machine learning initiatives from design to deployment, while mentoring a team of engineers and collaborating with cross-functional stakeholders. Roles and Responsibilities: Technical Leadership & Delivery Lead the end-to-end development of ML models and pipelines—from data preparation and feature engineering to model training, validation, and deployment. Translate business requirements into scalable ML solutions, ensuring performance, maintainability, and production readiness. Supervise and support team members in their project work; ensure adherence to coding and MLOps best practices. Model Development & Optimization Design and implement machine learning models (e.g., classification, regression, NLP, recommendation) using TensorFlow, PyTorch, or Scikit-learn. Optimize models for accuracy, latency, and efficiency through feature selection, hyperparameter tuning, and evaluation metrics. Conduct model performance analysis and guide the team in continuous improvement strategies. MLOps & Productionization Implement robust ML pipelines using MLflow, Kubeflow, or similar tools for CI/CD, monitoring, and lifecycle management. Work closely with DevOps and platform teams to containerize models and deploy them on cloud platforms like AWS SageMaker, GCP Vertex AI, or Azure ML. Ensure monitoring, alerting, and retraining strategies are in place for models in production. Team Collaboration & Mentorship Guide and mentor a team of ML engineers and junior data scientists. Collaborate closely with architects, data engineers, and product teams to ensure seamless integration of ML components. Contribute to code reviews, design sessions, and knowledge-sharing initiatives. Skills and Qualifications: Must-Have Skills 5+ years of experience in ML engineering or applied data science, with a strong track record of delivering production-grade ML systems. Deep expertise in Python, data structures, algorithms, and ML frameworks (TensorFlow, PyTorch, Scikit-learn). Hands-on experience with data pipeline tools (Airflow, Spark, Kafka, Pyspark) and MLOps platforms (MLflow, Kubeflow). Strong knowledge of cloud platforms (AWS, GCP, Azure) and containerization tools (Docker, Kubernetes). Solid understanding of model deployment, monitoring, and lifecycle management. Good-to-Have Skills Prior experience leading small to mid-sized technical teams. Exposure to business intelligence or data analytics. Cloud certifications (e.g., AWS Certified ML Specialty). Familiarity with agile methodologies and project tracking tools like Azure DevOps.

YES (Yield Engineering Systems, Inc.) is a leading manufacturer of reliable, high-tech, cost-effective capital equipment that transforms materials and surfaces at the nanoscale. From startups to the Fortune 50, our customers rely on YES to help them unleash products that change lives – from cellphones and IoT devices, to AI and virtual reality, to diagnostic tests for COVID. As a preferred provider of wet and dry process technology, we look forward to talking with smart, energetic, team-oriented people who can grow with us. We provide competitive salary and benefits, including long-term incentives, and some of the best co-workers you’ll find anywhere. If this appeals to you, please read on! Job Title: Data Applications Engineer Location: Coimbatore. We are seeking a highly skilled and motivated Data Applications Engineer with a minimum of a master’s degree in computer science, Engineering, or a closely related field. The successful candidate will be responsible for building, maintaining, and administrating data-driven applications to support the development of a digital twin for a semiconductor manufacturing company. This role demands advanced data science and computer vision expertise, alongside experience in C# programming, and involves designing systems that integrate engineering data, simulation results, image processing, and machine learning models to build predictive and autonomous capabilities. Responsibilities will include, but not be limited to: Design, develop, and deploy applications supporting the digital twin of semiconductor manufacturing processes. Develop automated data analysis tools and visualizations for engineers and operations teams. Integrate and analyse data from multiple sources (sensor data, imaging systems, databases, physics-based simulations, etc.) to derive insights and drive system performance. Apply computer vision and image processing techniques to enhance the digital twin's capability to mirror real-world environments and equipment. Work closely with engineering and business teams to define data requirements, perform data transformations, and ensure high-quality outputs. Build data pipelines and infrastructures for reliable, scalable, and secure data flow. Develop and deploy machine learning models for prediction, classification, anomaly detection, and optimization tasks. Understand CFD & FEA simulation outputs and incorporate into Digital Twin system. Write well-documented, efficient code in Python and C# for data processing and algorithmic implementations. Monitor, troubleshoot, and resolve issues related to data integration, system performance, and application stability. Create and maintain detailed documentation of data flows, algorithms, application logic, and technical implementations. Ensure data security, compliance, and governance standards are met. Present analysis and simulation results to stakeholders in a clear, structured format. Continuous research and apply best practices in digital twin development, machine learning, and computer vision. Required Qualifications: Minimum of a master’s degree in computer science, Data Science, Engineering, or a related discipline. Proven experience in designing and deploying machine learning models and computer vision solutions. Strong proficiency in Python (NumPy, Pandas, Scikit-learn, TensorFlow/PyTorch, OpenCV, Matplotlib). Hands-on experience with C# programming for application development and integration. Solid understanding of statistics, data structures, and algorithms. Ability to perform exploratory data analysis, data cleaning, and feature engineering. Knowledge of techniques such as classification, regression, anomaly detection, and optimisation. Experience with SQL for data handling and querying. Familiarity with version control tools such as GIT or Bitbucket. Strong analytical skills and the ability to work with structured and unstructured data from complex systems. Preferred Qualifications: Professional experience with digital twin technologies, particularly in semiconductor or advanced manufacturing sectors. Experience with CFD tools (ANSYS, Fluent, COMSOL, Star-CCM+) is a plus. Knowledge of Generative AI and NLP is a strong plus. Experience working in cross-functional teams and delivering production-level software solutions. Research experience involving machine learning applications to solve real-world engineering or manufacturing problems. Experience deploying and managing machine learning models in production using tools like MLflow, Kubeflow, or Airflow. Familiarity with CI/CD pipelines, Docker/Kubernetes, and cloud platforms (AWS, Azure, or GCP) for automating and scaling ML workflows. Understanding of model monitoring, versioning, and performance tracking to ensure reliability and reproducibility in production environments. Compensation: YES offers a stimulating and fun working environment, competitive salaries and benefits, and long-term incentives. Additional Information: YES is an equal opportunity employer and values diversity. All employment is decided based on qualifications, merit and business need. Come to find out why YES is such a great place to work. Apply today!

Role**: Digital : Data Science Required Technical Skill Set: Data Scientist Desired Experience Range: 03 - 08 yrs Notice Period: Immediate to 30Days only Location of Requirement: Hyderabad/Kolkata/Bangalore/Chennai/Pune We are currently planning to do a Virtual Interview Job Description: Must-Have** (Ideally should not be more than 3-5) Proficiency in Python or R for data analysis and modeling. Strong understanding of machine learning algorithms (regression, classification, clustering, etc.). Experience with SQL and working with relational databases. Hands-on experience with data wrangling, feature engineering, and model evaluation techniques. Experience with data visualization tools like Tableau, Power BI, or matplotlib/seaborn. Strong understanding of statistics and probability. Ability to translate business problems into analytical solutions. Good-to-Have Experience with deep learning frameworks (TensorFlow, Keras, PyTorch). Knowledge of big data platforms (Spark, Hadoop, Databricks). Experience deploying models using MLflow, Docker, or cloud platforms (AWS, Azure, GCP). Familiarity with NLP, computer vision, or time series forecasting. Exposure to MLOps practices for model lifecycle management. Understanding of data privacy and governance concepts. SN Responsibility of / Expectations from the Role 1 Work with stakeholders to identify business requirements and opportunities for leveraging data. Design and implement advanced analytics models using machine learning and statistical techniques. Clean, process, and analyze large datasets from various sources (structured & unstructured). Develop, test, and deploy predictive models and data pipelines. Create data visualizations, dashboards, and reports to communicate insights to non-technical users. Collaborate with data engineers, analysts, and product teams to integrate models into production environments. Monitor and continuously improve model performance. Stay up-to-date with latest research, tools, and techniques in data science and AI.

Job Title: Deliver Leader – Analytics and Data Science Department: Digital Services Reports to: Vice President Band: AVP Kindly click on the link below to apply: https://forms.office.com/r/zsjy1bD9yf Main Purpose of job We are looking for a dynamic leader qualified in solving problems with the power of analytics to join our Digital Services team. The Analytics and Data Science team is an integral part of our strategy to deliver superior value to our clients combined with the immense knowledge of the industries we operate in. As the leader for Analytics and Data science, you will be working with a team of highly motivated and insightful colleagues, in an entrepreneurial environment and play a crucial role in identifying, building and deploying analytics solutions that drive strategic goals of customers. This is an expanding team to deliver multi-million-dollar projects. You must have the ability to collaborate across various business segments within the organization to drive change and deliver value. Key responsibilities: · Have the experience and expertise in leveraging analytics for prediction and forecasting, data analysis, visualization with various sources – predominantly image and text data · Collaborate with cross-functional teams to support solutioning for proposals, planning and execution of programs. · Establishing credibility by thought partnering with pre-sales and customer teams on analytics topics · Communicating analytical insights through sophisticated synthesis and packaging of results (including PowerPoint presentation, Documents, dashboard and charts) · Support build collateral of documents to enhance core capabilities and supporting reference for internal documents · Ability to support business development activities (proposals, etc.) and build sales collateral to generate leads · Contributes to team's content & IP development; Mentor team on analytical methodologies and platforms and help in quality checks; Plan training needs of teams and work with corresponding teams to ensure training programs are delivered. · Develop and implement analytics strategies, frameworks, and best practices to ensure accurate data collection, analysis, and reporting. · Define and document data governance policies and procedures to ensure data quality, security, and compliance with regulations. · Conduct regular audits and assessments of analytics implementations, identifying gaps, errors, and opportunities for improvement. · Define and track key performance indicators (KPIs) and metrics to measure the success of digital marketing campaigns and website performance. · Stay updated with emerging trends and advancements in web analytics and data architecture, recommending and implementing innovative solutions to enhance analytics capabilities. Technical skills: · Strong proficiency in statistics (concepts & methodologies like hypothesis testing, sampling, etc.) and its application & interpretation · Hands-on data mining and predictive modeling experience (Linear Regression, Clustering (K-means, DBSCAN, etc.), Classification (Logistic regression, Decision trees/Random Forest/Boosted Trees), Timeseries (SARIMAX) etc. · Strong experience in at least one of the prominent cloud providers (Azure, AWS, GCP) and working knowledge of auto ML solutions (Sage Maker, Azure ML, Databricks etc.) · At least one tool in each category: o Programming language - Python (Must have), (R Or SAS OR PySpark), SQL (Must have) o Data Visualization (Tableau, QlikView, Power BI, Streamlit) , o Data management (using Alteryx, MS Access, or any RDBMS) o ML Deployment tools (Airflow, MLflow Luigi, Docker etc.) o Version Control (Git/Github/Git Lab) o MS Office (Excel, PowerPoint, Word) o Coding IDE (VS Code/PyCharm) o Nice to have: § Big data technologies (Hadoop ecosystem, Spark) § Data warehouse solutions (Teradata, Azure SQL DW/Synapse, Redshift, BigQuery etc,) § GenAI tools (OpenAI, Google PaLM/BERT, Hugging Face, etc.) Experience · Proven experience (15+ years) in analytics, ML, BI, AI and data modeling. · Strong understanding of data analytics tools and technologies, tools, and best practices, hands-on experience in applying appropriate analytics techniques to build statistical models, including handling of all pre- and post-modeling deliverables · Working knowledge of Python and SQL. Hands-on knowledge of any of the visualization tools amongst Power BI/Tableau · Experience across structured and unstructured data (text) leveraging classification, regression, unsupervised, NLP and other techniques · Excellent problem-solving and analytical skills, with the ability to think strategically and provide data-driven insights. Desired requirements: · Exposure to Process Mining platforms, concepts · Experience in working with Operations and business teams in a BPO environment.

Job Title: Machine Learning Engineer Location: 100% Remote Job Type: Full-Time About the Role: We are seeking a highly skilled and motivated Machine Learning Engineer to design, develop, and deploy cutting-edge ML models and data-driven solutions. You will work closely with data scientists, software engineers, and product teams to bring AI-powered products to life and scale them effectively. Key Responsibilities: Design, build, and optimize machine learning models for classification, regression, recommendation, and NLP tasks. Collaborate with data scientists to transform prototypes into scalable, production-ready models. Deploy, monitor, and maintain ML pipelines in production environments. Perform data preprocessing, feature engineering, and selection from structured and unstructured data. Implement model performance evaluation metrics and improve accuracy through iterative tuning. Work with cloud platforms (AWS, Azure, GCP) and MLOps tools to manage model lifecycle. Maintain clear documentation and collaborate cross-functionally across teams. Stay updated with the latest ML/AI research and technologies to continuously enhance our solutions. Required Qualifications: Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field. 2–5 years of experience in ML model development and deployment. Proficient in Python and libraries such as scikit-learn, TensorFlow, PyTorch, pandas, NumPy, etc. Strong understanding of machine learning algorithms, statistical modeling, and data analysis. Experience with building and maintaining ML pipelines using tools like MLflow, Kubeflow, or Airflow. Familiarity with containerization (Docker), version control (Git), and CI/CD for ML models. Experience with cloud services such as AWS SageMaker, GCP Vertex AI, or Azure ML.