337 Quantization Jobs - Page 2

Humanli.AI is a Startup founded by Alumnus of IIM' Bangalore/ISB Hyderabad & IIM' Calcutta. We are democratizing and extending technology that were accessible & consumed only by MNC’s or Fortune companies to SME and Mid-size firms. We are pioneers in bringing Knowledge Management algorithms & Large Language Models into Conversational BOT framework. Job Title: AI/ML Engineer Location: Jaipur Job Type: Full-time Experience: 0-3 years Job Description: We are looking for an experienced AI/ML & Data Engineer to join our team and contribute to the development and deployment of our AI-based solutions. As an AI/ML & Data Engineer, you will be responsible for designing and implementing data models, algorithms, and pipelines for training and deploying machine learning models. Responsibilities: Design, develop, and fine-tune Generative AI models (e.g., LLMs, GANs, VAEs, Diffusion Models). Implement Retrieval-Augmented Generation (RAG) pipelines using vector databases (FAISS, Pinecone, ChromaDB, Weaviate). Develop and integrate AI Agents for task automation, reasoning, and decision-making. Work on fine-tuning open-source LLMs (e.g., LLaMA, Mistral, Falcon) for specific applications. Optimize and deploy transformer-based architectures for NLP and vision-based tasks. Train models using TensorFlow, PyTorch, Hugging Face Transformers. Work on prompt engineering, instruction tuning, and reinforcement learning (RLHF). Collaborate with data scientists and engineers to integrate models into production systems. Stay updated with the latest advancements in Generative AI, ML, and DL. Optimize models for performance improvements, including quantization, pruning, and low-latency inference techniques. Qualification: B.Tech in Computer Science. Fresher's may apply 0-3 years of experience in data engineering and machine learning. Immediate joiners: Preferred Requirement Experience with data preprocessing, feature engineering, and model evaluation. Understanding of transformers, attention mechanisms, and large-scale training. Hands-on experience with, RAG, LangChain/LangGraph, LlamaIndex, and other agent frameworks. Understanding of prompt tuning, LoRA/QLora, and efficient parameter fine-tuning (PEFT) techniques. Strong knowledge of data modeling, data preprocessing, and feature engineering techniques. Experience with cloud computing platforms such as AWS, Azure, or Google Cloud Platform. Excellent problem-solving skills and ability to work independently and collaboratively in a team environment. Strong communication skills and ability to explain technical concepts to non-technical stakeholders.

As a Senior AI Engineer with React Native expertise, you will be responsible for developing and integrating AI features using various LLMs such as Norah AI, OpenAI GPT, Google Gemini, and Claude. Your tasks will include creating AI-driven onboarding processes, recommendations, virtual assistants, and news digests. Additionally, you will implement instant voice translation through the Google Translate API, personalized notifications based on user preferences and location, and optimize AI models for mobile platforms like TensorFlow Lite and Core ML to ensure low latency, offline support, and battery efficiency. In the realm of React Native front-end development, you will be tasked with building responsive, cross-platform UI/UX features such as onboarding flows, event booking systems, concierge chat interfaces, and navigation components. You will integrate real-time functionalities like WebSockets, Firebase push notifications, and third-party APIs such as Almosafer, BlackLane, Uber, BLE beacons, and Marcom. Ensuring accessibility, security measures like OAuth and JWT, and cultural alignment for example, understanding Saudi etiquette will also be crucial aspects of your responsibilities. Your role will involve feature implementation across various areas including onboarding and personalization, booking and planning, concierge services and AI assistant functionalities, navigation and real-time capabilities, engagement and security features, as well as admin support for analytics, event monitoring, and emergency alerts. You will be required to test AI accuracy, bias, and mobile performance, optimizing for offline usage, real-time updates, and accessibility. Collaboration with cross-functional teams to align with MoT protocols and documenting AI pipelines and React Native code will be essential parts of your job. To qualify for this position, you should have at least 5 years of experience in AI engineering, with a minimum of 3 years of experience integrating AI into React Native mobile apps for iOS and Android platforms. You should possess expertise in AI/ML frameworks like TensorFlow, PyTorch, and Hugging Face, as well as familiarity with LLMs such as OpenAI and Google Gemini. Proficiency in React Native, JavaScript/TypeScript, Redux, and UI libraries like React Native Elements is required. Strong skills in API integrations, voice APIs like Google Translate, real-time systems, and secure authentication methods are also necessary. Knowledge of mobile AI optimization techniques and navigation technologies is a plus. A Bachelor's or Master's degree in Computer Science, AI/ML, or a related field is preferred for this role. In addition to technical skills, you should have strong problem-solving abilities, collaboration skills, and effective communication with both technical and non-technical stakeholders. This is a full-time position located in person. When applying, please specify your notice period and total experience of 4 years.,

Position title Lead Engineer - AI/ML Description Prospus Consulting Pvt. Ltd. is a fully remote IT consulting company specializing in SaaS solutions. We are looking to hire a highly skilled and experienced Lead AI/ML Engineer to focus on AI-enabling a SaaS application. If you have a passion for innovation and a proven track record in AI/ML software development, we invite you to join our team. Responsibilities Lead the development and integration of AI/ML capabilities into a SaaS application. Design, train, fine-tune, and deploy large language models (LLMs) using advanced embedding techniques. Develop and implement Natural Language Processing (NLP) solutions, including tokenization, attention mechanisms, and sentiment analysis. Perform tasks such as text summarization, semantic search, and supervised/unsupervised learning. Optimize AI/ML models using techniques like quantization, pruning, and distillation. Create and manage searchable vector databases derived from extensive knowledge bases. Build and deploy intelligent chatbots to enhance user experience. Collaborate with cross-functional teams to define project requirements and deliver AI-enabled features. Evaluate model performance using industry-standard metrics and implement improvements as needed. Skills 6+ years of experience in AI/ML software development. Hands-on experience with LLM fine-tuning and embedding techniques. Proficiency in NLP frameworks, tokenization, and attention mechanisms. Demonstrated expertise in sentiment analysis, text summarization, and semantic search. Strong knowledge of supervised and unsupervised learning methodologies. Experience in model distillation and optimization (e.g., quantization, pruning). Hands-on experience with Hugging Face transformers. Proficiency in Python for AI/ML applications. Proven track record of building chatbots and conversational AI systems. Experience creating searchable vector databases from large knowledge bases. Expertise in evaluating model performance and using appropriate metrics. Qualifications Familiarity with AI/ML applications in SaaS platforms. Experience working with remote teams and agile methodologies. Strong problem-solving and analytical skills. Contacts To apply for this position, please complete the mandatory application form linked below. Only applications that include submission of this form will be considered. We appreciate your understanding and look forward to reviewing your application! Submit Your Application Here

Position Overview- We are looking for an experienced AI Engineer to design, build, and optimize AI-powered applications, leveraging both traditional machine learning and large language models (LLMs). The ideal candidate will have a strong foundation in LLM fine-tuning, inference optimization, backend development, and MLOps, with the ability to deploy scalable AI systems in production environments. ShyftLabs is a leading data and AI company, helping enterprises unlock value through AI-driven products and solutions. We specialize in data platforms, machine learning models, and AI-powered automation, offering consulting, prototyping, solution delivery, and platform scaling. Our Fortune 500 clients rely on us to transform their data into actionable insights. Key Responsibilities: Design and implement traditional ML and LLM-based systems and applications Optimize model inference for performance and cost-efficiency Fine-tune foundation models using methods like LoRA, QLoRA, and adapter layers Develop and apply prompt engineering strategies including few-shot learning, chain-of-thought, and RAG Build robust backend infrastructure to support AI-driven applications Implement and manage MLOps pipelines for full AI lifecycle management Design systems for continuous monitoring and evaluation of ML and LLM models Create automated testing frameworks to ensure model quality and performance Basic Qualifications: Bachelor’s degree in Computer Science, AI, Data Science, or a related field 4+ years of experience in AI/ML engineering, software development, or data-driven solutions LLM Expertise Experience with parameter-efficient fine-tuning (LoRA, QLoRA, adapter layers) Understanding of inference optimization techniques: quantization, pruning, caching, and serving Skilled in prompt engineering and design, including RAG techniques Familiarity with AI evaluation frameworks and metrics Experience designing automated evaluation and continuous monitoring systems Backend Engineering Strong proficiency in Python and frameworks like FastAPI or Flask Experience building RESTful APIs and real-time systems Knowledge of vector databases and traditional databases Hands-on experience with cloud platforms (AWS, GCP, Azure) focusing on ML services MLOps & Infrastructure Familiarity with model serving tools (vLLM, SGLang, TensorRT) Experience with Docker and Kubernetes for deploying ML workloads Ability to build monitoring systems for performance tracking and alerting Experience building evaluation systems using custom metrics and benchmarks Proficient in CI/CD and automated deployment pipelines Experience with orchestration tools like Airflow Hands-on experience with LLM frameworks (Transformers, LangChain, LlamaIndex) Familiarity with LLM-specific monitoring tools and general ML monitoring systems Experience with distributed training and inference on multi-GPU environments Knowledge of model compression techniques like distillation and quantization Experience deploying models for high-throughput, low-latency production use Research background or strong awareness of the latest developments in LLMs Tools & Technologies We Use Frameworks: PyTorch, TensorFlow, Hugging Face Transformers Serving: vLLM, TensorRT-LLM, SGlang, OpenAI API Infrastructure: Docker, Kubernetes, AWS, GCP Databases: PostgreSQL, Redis, Vector Databases We are proud to offer a competitive salary alongside a strong healthcare insurance and benefits package. We pride ourselves on the growth of our employees, offering extensive learning and development resources.

Job Title: AI & ML Developer (Python) Company: ChicMic Studios Location: Mohali, Punjab (Hybrid Options Available) Job Type: Full-Time | 5 Days Working Experience Required: 5+ Years Immediate Joiners Preferred Job Summary: ChicMic Studios is seeking an experienced and innovative AI/ML Developer with strong expertise in Python-based web development and machine learning. The ideal candidate will have 5+ years of hands-on experience with Django, Flask , and cloud deployment on AWS , along with a solid understanding of transformer architectures , model deployment , and MLOps practices . Key Responsibilities: Develop and maintain robust web applications using Django and Flask Build and manage scalable RESTful APIs using Django Rest Framework (DRF) Deploy, manage, and optimize applications using AWS services : EC2, S3, Lambda, RDS, etc. Design and integrate AI/ML APIs into production systems Build ML models using PyTorch, TensorFlow, Scikit-learn Implement transformer architectures like BERT, GPT for NLP and vision tasks Apply model optimization techniques: quantization, pruning, hyperparameter tuning Deploy models using SageMaker, TorchServe, TensorFlow Serving Ensure high performance and scalability of deployed AI systems Collaborate with cross-functional teams to deliver scalable AI-powered products Follow clean coding practices, conduct code reviews, and stay current with AI/ML advancements Required Skills & Qualifications: Btech/ MCA 5+ years of Python development experience Expertise in Django , Flask , and DRF Solid experience deploying apps and models on AWS Proficiency in PyTorch , TensorFlow , and Scikit-learn Experience with transformer models (BERT, GPT, etc.) Strong knowledge of SQL and NoSQL databases (PostgreSQL, MongoDB) Familiarity with MLOps practices for end-to-end model management Bonus: Basic front-end skills (JavaScript, HTML, CSS) Excellent communication and problem-solving skills Why Join ChicMic Studios? Global exposure across 16+ modern tech stacks High retention culture and innovation-driven environment Opportunity to work on cutting-edge AI/ML and NLP projects EPF, Earned Leaves, Career Growth Support Hybrid/WFH flexibility for exceptional candidates To Apply: Send your resume to: disha.mehta755@chicmicstudios.in Contact: +91 98759 52834 Website: www.chicmicstudios.in Job Type: Full-time Pay: ₹800,000.00 - ₹1,800,000.00 per year Benefits: Flexible schedule Provident Fund Work from home Education: Bachelor's (Required) Experience: Python: 5 years (Required) AI: 2 years (Required) Language: English (Required) Work Location: In person

Job Title: AI & ML Developer (Python) Company: ChicMic Studios Location: Mohali, Punjab (Hybrid Options Available) Job Type: Full-Time | 5 Days Working Experience Required: 5+ Years Immediate Joiners Preferred Job Summary: ChicMic Studios is seeking an experienced and innovative AI/ML Developer with strong expertise in Python-based web development and machine learning. The ideal candidate will have 5+ years of hands-on experience with Django, Flask , and cloud deployment on AWS , along with a solid understanding of transformer architectures , model deployment , and MLOps practices . Key Responsibilities: Develop and maintain robust web applications using Django and Flask Build and manage scalable RESTful APIs using Django Rest Framework (DRF) Deploy, manage, and optimize applications using AWS services : EC2, S3, Lambda, RDS, etc. Design and integrate AI/ML APIs into production systems Build ML models using PyTorch, TensorFlow, Scikit-learn Implement transformer architectures like BERT, GPT for NLP and vision tasks Apply model optimization techniques: quantization, pruning, hyperparameter tuning Deploy models using SageMaker, TorchServe, TensorFlow Serving Ensure high performance and scalability of deployed AI systems Collaborate with cross-functional teams to deliver scalable AI-powered products Follow clean coding practices, conduct code reviews, and stay current with AI/ML advancements Required Skills & Qualifications: Btech/ MCA 5+ years of Python development experience Expertise in Django , Flask , and DRF Solid experience deploying apps and models on AWS Proficiency in PyTorch , TensorFlow , and Scikit-learn Experience with transformer models (BERT, GPT, etc.) Strong knowledge of SQL and NoSQL databases (PostgreSQL, MongoDB) Familiarity with MLOps practices for end-to-end model management Bonus: Basic front-end skills (JavaScript, HTML, CSS) Excellent communication and problem-solving skills Why Join ChicMic Studios? Global exposure across 16+ modern tech stacks High retention culture and innovation-driven environment Opportunity to work on cutting-edge AI/ML and NLP projects EPF, Earned Leaves, Career Growth Support Hybrid/WFH flexibility for exceptional candidates To Apply: Send your resume to: disha.mehta755@chicmicstudios.in Contact: +91 98759 52834 Website: www.chicmicstudios.in Job Type: Full-time Pay: ₹800,000.00 - ₹1,800,000.00 per year Benefits: Flexible schedule Provident Fund Work from home Education: Bachelor's (Required) Experience: Python: 5 years (Required) AI: 2 years (Required) Language: English (Required) Work Location: In person

Job Description: 7–10 years of industry experience, with at least 5 years in machine learning roles. Advanced proficiency in Python and common ML libraries: TensorFlow, PyTorch, Scikit-learn. Experience with distributed training, model optimization (quantization, pruning), and inference at scale. Hands-on experience with cloud ML platforms: AWS (SageMaker), GCP (Vertex AI), or Azure ML. Familiarity with MLOps tooling: MLflow, TFX, Airflow, or Kubeflow; and data engineering frameworks like Spark, dbt, or Apache Beam. Strong grasp of CI/CD for ML, model governance, and post-deployment monitoring (e.g., data drift, model decay). Excellent problem-solving, communication, and documentation skills.

Build the AI Reasoning Layer for Education We’re reimagining the core intelligence layer for education —tackling one of the most ambitious challenges in AI: subjective assessment automation and ultra-personalized learning at scale. This isn’t just another LLM application. We’re building a first-principles AI reasoning engine combining multi-modal learning, dynamic knowledge graphs, and real-time content generation . The goal? To eliminate billions of wasted hours in manual evaluation and create an AI that understands how humans learn . As a Founding AI Engineer , you’ll define and build this system from the ground up. You’ll work on problems few have attempted, at the bleeding edge of LLMs, computer vision, and generative reasoning. What You’ll Be Solving: Handwriting OCR at near-human accuracy: How can we push vision-language models to understand messy, real-world input from students? Real-time learner knowledge modeling: Can AI track and reason about what someone knows—and how they’re learning—moment to moment? Generative AI that teaches: How do we create dynamic video lessons that evolve in sync with a learner’s knowledge state? Scalable inference infrastructure: How do we optimize LLMs and multimodal models to support millions of learners in real time? What You’ll Be Building: Architect, deploy & optimize multi-modal AI systems—OCR, knowledge-state inference, adaptive content generation. Build reasoning engines that combine LLMs, retrieval, and learner data to dynamically guide learning. Fine-tune foundation models (LLMs, VLMs) and implement cutting-edge techniques (quantization, LoRA, RAG, etc.). Design production-grade AI systems: modular, scalable, and optimized for inference at global scale. Lead experiments at the frontier of AI research, publishing if desired. Tech Stack & Skills Must-Have: Deep expertise in AI/ML, with a focus on LLMs, multi-modal learning, and computer vision. Hands-on experience with OCR fine-tuning and handwritten text recognition Strong proficiency in AI frameworks: PyTorch, TensorFlow, Hugging Face, OpenCV. Experience in optimizing AI for production: LLM quantization, retrieval augmentation, and MLOps. Knowledge graphs and AI-driven reasoning systems experience Nice-to-Have: Experience with Diffusion Models, Transformers, and Graph Neural Networks (GNNs). Expertise in vector databases, real-time inference pipelines, and low-latency AI deployment. Prior experience in ed-tech, adaptive learning AI, or multi-modal content generation. Why This Role Is Rare Define the AI stack for a category-defining product at inception. Work with deep ownership across research, engineering, and infrastructure. Founding-level equity and influence in a high-growth company solving a $100B+ problem. Balance of cutting-edge research and real-world deployment. Solve problems that matter —not just academically, but in people’s lives. Who this role is for This is for builders at the edge—engineers who want to architect, not just optimize. Researchers who want their ideas shipped.If you want to: Push LLMs, CV, and multimodal models to their performance limits. Build AI that learns, reasons, and adapts like a human tutor. Shape the foundational AI layer for education

As a Senior Machine Learning Engineer at TrueFan, you will be at the forefront of AI-driven content generation, leveraging cutting-edge generative models to build next-generation products. Your mission will be to redefine the content generation space through advanced AI technologies, including deep generative models, text-to-video, image-to-video, and lipsync generation. Your responsibilities will include designing, developing, and deploying cutting-edge models for end-to-end content generation. This will involve working on the latest advancements in deep generative modeling to create highly realistic and controllable AI-generated media. You will research and develop state-of-the-art generative models such as Diffusion Models, 3D VAEs, and GANs for AI-powered media synthesis. Additionally, you will build and optimize AI pipelines for high-fidelity image/video generation and lipsyncing using diffusion and autoencoder models. Furthermore, you will be responsible for developing advanced lipsyncing and multimodal generation models that integrate speech, video, and facial animation for hyper-realistic AI-driven content. Your role will also involve implementing and optimizing models for real-time content generation and interactive AI applications using efficient model architectures and acceleration techniques. Collaboration with software engineers to deploy models efficiently on cloud-based architectures will be a key aspect of your work. To qualify for this role, you should have a Bachelor's or Master's degree in Computer Science, Machine Learning, or a related field, along with 3+ years of experience working with deep generative models like Diffusion Models, 3D VAEs, GANs, and autoregressive models. Proficiency in Python and deep learning frameworks such as PyTorch is essential. Strong problem-solving abilities, a research-oriented mindset, and familiarity with generative adversarial techniques are also required. Preferred qualifications include experience with transformers and vision-language models, background in text-to-video generation and lipsync generation, expertise in cloud-based AI pipelines, and contributions to open-source projects or published research in AI-generated content. If you are passionate about AI-driven content generation and have a strong background in generative AI, this is the perfect opportunity for you to drive research and development in AI-generated content and real-time media synthesis at TrueFan.,

About Us QuillBot is an AI-powered writing platform on a mission to reimagine writing. QuillBot provides over 50 million monthly active uses students, professionals, and educators with free online writing and research tools to help them become more effective, productive, and confident. The QuillBot team was built on the idea that learning how to write and use that knowledge is empowering. They want to automate the more time-consuming parts of writing so that users can focus on their craft. Whether you're writing essays, social media posts, or emails, QuillBot has your back. It has an array of productivity-enhancing tools that are already changing the way the world writes. In the recent chain of events, we were also acquired by CourseHero, which is a 15-year-old Ed-Tech unicorn based out of California, now known as Learneo. Overview QuillBot is looking for a hands-on MLOps Manager to lead and scale our AI Engineering & MLOps function. This role blends deep technical execution (60%) with team and cross-functional collaboration (40%), and is ideal for someone who thrives in a dual IC + strategic lead position. You'll work closely with Research, Platform, Infra, and Product teams — not only to deploy models reliably, but also to accelerate experimentation, training, and iteration cycles. From infra support for large-scale model training to scaling low-latency inference systems in production, you'll be at the heart of how AI ships at QuillBot. Responsibilities Own the full ML lifecycle: from training infra and experiment tracking to deployment, observability, and optimization. Work closely with researchers to remove friction in training, evaluation, and finetuning workflows. Guide and mentor a small, mature team of engineers (3–4), while still contributing as an individual contributor. Drive performance optimization (latency, throughput, cost efficiency), model packaging, and runtime reliability. Build robust systems for CI/CD, versioning, rollback, A/B testing, monitoring, and alerting. Ensure scalable, secure, and compliant AI infrastructure across training and inference environments. Collaborate with cloud and AI providers (e.g., AWS, GCP, OpenAI) as needed to integrate tooling, optimize costs, and unlock platform capabilities. Contribute to other GenAI and cross-functional AI initiatives as needed, beyond core MLOps responsibilities. Contribute to architectural decisions, roadmap planning, and documentation of our AI engineering stack. Champion automation, DevOps/MLOps best practices, and technical excellence across the ML lifecycle. Qualifications 5+ years of strong experience in MLOps, ML/AI Engineering. Solid understanding of ML/DL fundamentals and applied experience in model deployment and training infra. Proficient with cloud-native ML tooling (e.g., GCP, Vertex AI, Kubernetes). Comfortable working on both training-side infra and inference-side systems. Good to have experience with model optimization techniques (e.g., quantization, distillation, FasterTransformer, TensorRT-LLM). Proven ability to lead complex technical projects end-to-end with minimal oversight. Strong collaboration and communication skills — able to work cross-functionally and drive technical clarity. Ownership mindset — comfortable making decisions and guiding others in ambiguous problem spaces." Benefits & Perks Competitive salary, stock options & annual bonus Medical coverage Life and accidental insurance Vacation & leaves of absence (menstrual, flexible, special, and more!) Developmental opportunities through education & developmental reimbursements & professional workshops Maternity & parental leave Hybrid & remote model with flexible working hours On-site & remote company events throughout the year Tech & WFH stipends & new hire allowances Employee referral program Premium access to QuillBot Benefits and benefit amounts differ by region. A comprehensive list applicable to your region will be provided in your interview process. Research shows that candidates from underrepresented backgrounds often don't apply for roles if they don't meet all the criteria. We strongly encourage you to apply if you're interested: we'd love to learn how you can amplify our team with your unique experience! This role is eligible for hire in India. We are a virtual-first company and have employees dispersed throughout the United States, Canada, India and the Netherlands. We have a market-based pay structure that varies by location. The base pay for this position is dependent on multiple factors, including candidate experience and expertise, and may vary from the amounts listed. You may also be eligible to participate in our bonus program and may be offered benefits, and other types of compensation. #QuillBot Equal Employment Opportunity Statement (EEO) We are an equal opportunity employer and value diversity and inclusion within our company. We will consider all qualified applicants without regard to race, religion, color, national origin, sex, gender identity, gender expression, sexual orientation, age, marital status, veteran status, or ability status. We will ensure that individuals who are differently abled are provided 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 as provided to other applicants or employees. Please contact us to request accommodation.

About Us QuillBot is an AI-powered writing platform on a mission to reimagine writing. QuillBot provides over 50 million monthly active uses students, professionals, and educators with free online writing and research tools to help them become more effective, productive, and confident. The QuillBot team was built on the idea that learning how to write and use that knowledge is empowering. They want to automate the more time-consuming parts of writing so that users can focus on their craft. Whether you're writing essays, social media posts, or emails, QuillBot has your back. It has an array of productivity-enhancing tools that are already changing the way the world writes. In the recent chain of events, we were also acquired by CourseHero, which is a 15-year-old Ed-Tech unicorn based out of California, now known as Learneo. Overview QuillBot is looking for a hands-on MLOps Manager to lead and scale our AI Engineering & MLOps function. This role blends deep technical execution (60%) with team and cross-functional collaboration (40%), and is ideal for someone who thrives in a dual IC + strategic lead position. You'll work closely with Research, Platform, Infra, and Product teams — not only to deploy models reliably, but also to accelerate experimentation, training, and iteration cycles. From infra support for large-scale model training to scaling low-latency inference systems in production, you'll be at the heart of how AI ships at QuillBot. Responsibilities Own the full ML lifecycle: from training infra and experiment tracking to deployment, observability, and optimization. Work closely with researchers to remove friction in training, evaluation, and finetuning workflows. Guide and mentor a small, mature team of engineers (3–4), while still contributing as an individual contributor. Drive performance optimization (latency, throughput, cost efficiency), model packaging, and runtime reliability. Build robust systems for CI/CD, versioning, rollback, A/B testing, monitoring, and alerting. Ensure scalable, secure, and compliant AI infrastructure across training and inference environments. Collaborate with cloud and AI providers (e.g., AWS, GCP, OpenAI) as needed to integrate tooling, optimize costs, and unlock platform capabilities. Contribute to other GenAI and cross-functional AI initiatives as needed, beyond core MLOps responsibilities. Contribute to architectural decisions, roadmap planning, and documentation of our AI engineering stack. Champion automation, DevOps/MLOps best practices, and technical excellence across the ML lifecycle. Qualifications 5+ years of strong experience in MLOps, ML/AI Engineering. Solid understanding of ML/DL fundamentals and applied experience in model deployment and training infra. Proficient with cloud-native ML tooling (e.g., GCP, Vertex AI, Kubernetes). Comfortable working on both training-side infra and inference-side systems. Good to have experience with model optimization techniques (e.g., quantization, distillation, FasterTransformer, TensorRT-LLM). Proven ability to lead complex technical projects end-to-end with minimal oversight. Strong collaboration and communication skills — able to work cross-functionally and drive technical clarity. Ownership mindset — comfortable making decisions and guiding others in ambiguous problem spaces." Benefits & Perks Competitive salary, stock options & annual bonus Medical coverage Life and accidental insurance Vacation & leaves of absence (menstrual, flexible, special, and more!) Developmental opportunities through education & developmental reimbursements & professional workshops Maternity & parental leave Hybrid & remote model with flexible working hours On-site & remote company events throughout the year Tech & WFH stipends & new hire allowances Employee referral program Premium access to QuillBot Benefits and benefit amounts differ by region. A comprehensive list applicable to your region will be provided in your interview process. Research shows that candidates from underrepresented backgrounds often don't apply for roles if they don't meet all the criteria. We strongly encourage you to apply if you're interested: we'd love to learn how you can amplify our team with your unique experience! This role is eligible for hire in India. We are a virtual-first company and have employees dispersed throughout the United States, Canada, India and the Netherlands. We have a market-based pay structure that varies by location. The base pay for this position is dependent on multiple factors, including candidate experience and expertise, and may vary from the amounts listed. You may also be eligible to participate in our bonus program and may be offered benefits, and other types of compensation. #Learneo Equal Employment Opportunity Statement (EEO) We are an equal opportunity employer and value diversity and inclusion within our company. We will consider all qualified applicants without regard to race, religion, color, national origin, sex, gender identity, gender expression, sexual orientation, age, marital status, veteran status, or ability status. We will ensure that individuals who are differently abled are provided 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 as provided to other applicants or employees. Please contact us to request accommodation. About Learneo Learneo is a platform of builder-driven businesses, including Course Hero, CliffsNotes, LitCharts, Quillbot, Symbolab, and Scribbr, all united around a shared mission of supercharging productivity and learning for everyone. We attract and scale high growth businesses built and run by visionary entrepreneurs. Each team innovates independently but has a unique opportunity to collaborate, experiment, and grow together, and they are supported by centralized corporate operations functions, including HR, Finance and Legal.

Company Size Large-scale / Global Experience Required 3 - 5 years Working Days 6 days/week Office Location Viman Nagar, Pune Role & Responsibilities Agentic AI Development: Design and develop multi-agent conversational frameworks with adaptive decision-making capabilities. Integrate goal-oriented reasoning and memory components into agents using transformer-based architectures. Build negotiation-capable bots with real-time context adaptation and recursive feedback processing. Generative AI & Model Optimization: Fine-t une LLMs/SLMs using proprietary and domain-specific datasets (NBFC, Financial Services, etc.). Apply distillation and quantization for efficient deployment on edge devices. Benchmark LLM/SLM performance on server vs. edge environments for real-time use cases. Speech And Conversational Intelligence: Implement contextual dialogue flows using speech inputs with emotion and intent tracking. Evaluate and deploy advanced Speech-to-Speech (S2S) models for naturalistic voice responses. Work on real-time speaker diarization and multi-turn, multi-party conversation tracking. Voice Biometrics & AI Security: Train and evaluate voice biometric models for secure identity verification. Implement anti-spoofing layers to detect deepfakes, replay attacks, and signal tampering. Ensure compliance with voice data privacy and ethical AI guidelines. Self-Learning & Autonomous Adaptation: Develop frameworks for agents to self-correct and adapt using feedback loops without full retraining. Enable low-footprint learning systems on-device to support personalization on the edge. Ideal Candidate Educational Qualifications: Bachelors/Masters degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Experience Required: 35 years of experience, with a mix of core software development and AI/ML model engineering. Proven hands-on work with Conversational AI, Generative AI, or Multi-Agent Systems. Technical Proficiency: Strong programming in Python, TensorFlow/PyTorch, and model APIs (Hugging Face, LangChain, OpenAI, etc.). Expertise in STT, TTS, S2S, speaker diarization, and speech emotion recognition. LLM fine-tuning, model optimization (quantization, distillation), RAG pipelines. Understanding of agentic frameworks, cognitive architectures, or belief-desire-intention (BDI) models. Familiarity with Edge AI deployment, low-latency model serving, and privacy-compliant data pipelines. Desirable: Exposure to agent-based simulation, reinforcement learning, or behavioralmodeling. Publications, patents, or open-source contributions in conversational AI or GenAI systems. Perks, Benefits and Work Culture Our people define our passion and our audacious, incredibly rewarding achievements. Bajaj Finance Limited is one of Indias most diversified Non-banking financial companies, and among Asias top 10 Large workplaces. If you have the drive to get ahead, we can help find you an opportunity at any of the 500+ locations were present in India. Skills: edge ai deployment,adaptation,speech emotion recognition,llm fine-tuning,tensorflow,models,intelligence,model optimization,speech,speech-to-speech,data,openai,hugging face,llm,optimization,agents,langchain,pytorch,python Show more Show less

JD for Generative AI Specialist JD Junior / Senior Generative AI Specialist Year of experience Junior / Senior 4-6 Years or 6- 8 years Shift : 11AM - 8PM Location : Chennai. Mode : Work From Office Role -The Generative AI specialist should be building GenAI LLM model driven solution using State of the Art Models like ( OpenAI, Gemini, Claude) , Opensource Models ( llama, Mistral). Should have expertise in fine tuning and training models . Should have implemented projects with expertise on Agents, Tools and RAG solutions. Hands on expertise in integrating LLMs with VectorDB like chromadb, faiss, pinecone is required. Expertise in PEFT, Quantization of models is required. Experience in Tensorflow, Pytorch, Python, Hugging Face, Transformers is must. Expert in data preparation, analysis and hands one expertise in Deep Learning model development is preferred. Additional expertise in deploying models in AWS is desired but optional. Skills OpenAI, Gemini, LangChain, Transformers, Hugging Face, Python, Pytorch, Tensorflow, Vectordb( chromadb, faiss, pinecone) Project experience Atleast 1-2 live implementation of Generative AI driven solution implementation. Extensive experience in implementing chatbots, knowledge search and in NLP . Good expertise in implementing Machine learning and deep learning solutions for atleast 2 years. 4th Floor, Techno Park, 10, Rajiv Gandhi Salai, Customs Colony, Sakthi Nagar, Thoraipakkam, Chennai 600097 Skills: rag,nlp,aws,vectordb (chromadb, faiss, pinecone),claude,agents,tensorflow,langchain,chatbots,hugging face,analysis,transformers,python,chromadb,gemini,openai,deep learning,faiss,llms,opensource models,pytorch,genai llm,peft,machine learning,llama,vectordb,mistral,pinecone

Job purpose: Design, develop, and deploy end-to-end AI/ML systems, focusing on large language models (LLMs), prompt engineering, and scalable system architecture. Leverage technologies such as Java/Node.js/NET to build robust, high-performance solutions that integrate with enterprise systems. Who You Are: Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. PhD is a plus. 10+ years of experience in AI/ML development, with at least 2 years working on LLMs or NLP. Proven expertise in end-to-end system design and deployment of production-grade AI systems. Hands-on experience with Java/Node.js/.NET for backend development. Proficiency in Python and ML frameworks (TensorFlow, PyTorch, Hugging Face Transformers). Key Responsibilities: 1. Model Development & Training: Design, train, and fine-tune large language models (LLMs) for tasks such as natural language understanding, generation, and classification. Implement and optimize machine learning algorithms using frameworks like TensorFlow, PyTorch, or Hugging Face. 2. Prompt Engineering: Craft high-quality prompts to maximize LLM performance for specific use cases, including chatbots, text summarization, and question-answering systems. Experiment with prompt tuning and few-shot learning techniques to improve model accuracy and efficiency. 3. End-to-End System Design: Architect scalable, secure, and fault-tolerant AI/ML systems, integrating LLMs with backend services and APIs. Develop microservices-based architectures using Java/Node.js/.NET for seamless integration with enterprise applications. Design and implement data pipelines for preprocessing, feature engineering, and model inference. 4. Integration & Deployment: Deploy ML models and LLMs to production environments using containerization (Docker, Kubernetes) and cloud platforms (AWS/Azure/GCP). Build RESTful or GraphQL APIs to expose AI capabilities to front-end or third-party applications. 5. Performance Optimization: Optimize LLMs for latency, throughput, and resource efficiency using techniques like quantization, pruning, and model distillation. Monitor and improve system performance through logging, metrics, and A/B testing. 6. Collaboration & Leadership: Work closely with data scientists, software engineers, and product managers to align AI solutions with business objectives. Mentor junior engineers and contribute to best practices for AI/ML development. What will excite us: Strong understanding of LLM architectures and prompt engineering techniques. Experience with backend development using Java/Node.js (Express)/.NET Core. Familiarity with cloud platforms (AWS, Azure, GCP) and DevOps tools (Docker, Kubernetes, CI/CD). Knowledge of database systems (SQL, NoSQL) and data pipeline tools (Apache Kafka, Airflow). Strong problem-solving and analytical skills. Excellent communication and teamwork abilities. Ability to work in a fast-paced, collaborative environment. What will excite you: Lead AI innovation in a fast-growing, technology-driven organization. Work on cutting-edge AI solutions, including LLMs, autonomous AI agents, and Generative AI applications. Engage with top-tier enterprise clients and drive AI transformation at scale. Location: Ahmedabad

About Zupee We are the biggest online gaming company with largest market share in the Indian gaming sector’s largest segment — Casual & Boardgame. We make skill-based games that spark joy in the everyday lives of people by engaging, entertaining, and enabling earning while at play. In the three plus years of existence, Zupee has been on a mission to improve people’s lives by boosting their learning ability, skills, and cognitive aptitude through scientifically designed gaming experiences. Zupee presents a timeout from the stressful environments we live in today and sparks joy in the lives of people through its games. Zupee invests in people and bets on creating excellent user experiences to drive phenomenal growth. We have been running profitable at EBT level since Q3, 2020 while closing Series B funding at $102 million, at a valuation of $600 million. Zupee is all set to transform from a fast-growing startup to a firm contender for the biggest gaming studio in India.. ABOUT THE JOB Role: Senior Machine Learning Engineer Reports to: Manager- Data Scientist Location: Gurgaon Experience: 3-6 Years Role & Responsibilities 1) Managing the deployment and maintenance of machine learning models in production environments and ensuring seamless integration with existing systems. 2) Collaborate with ML teams to optimize models for inference performance, latency, and resource utilization. 3) Monitoring model performance using metrics such as accuracy, precision, recall, and F1 score, and addressing issues like performance degradation, drift, or bias. 4) Implement techniques such as model quantization, pruning, knowledge distillation, or hardware-specific optimizations (e.g., TensorRT, ONNX). 5) Architect, design, and develop reusable tools, libraries, and infrastructure to accelerate ML deployment and performance analysis for the broader organization. 6) Troubleshoot and resolve problems, maintain documentation, and manage model versions for audit and rollback. 7) Analyzing monitoring data to preemptively identify potential issues and providing regular performance reports to stakeholders. 8) Optimization of the queries and pipelines. Modernization of the applications whenever required. Must - Have Skills: 1) MlOps 2) Python 3) AWS 4) Bash 5) Kubernetes Desired Skills 1) Sagemaker 2) Triton 3) Nvidia 4) GPU 5) Model Optimization

As the AI Solutions Architect, you will be responsible for designing and implementing AI/ML solutions to advance the ZL Platform. Your role involves collaborating with stakeholders to identify business needs, proposing technical solutions, and overseeing the implementation of the chosen solutions. You will partner with Engineering, Product, and Sales teams to secure design wins at customers, enabling the development and growth of ZL product features through customer feedback and PoC evaluations. Additionally, you will be accountable for the success, quality, and timely delivery of AI/ Machine Learning components. Acting as a problem solver, you will address organizational and process challenges by leveraging your technical expertise to bridge gaps, streamline operations, and facilitate the smooth execution of partnership initiatives. It is crucial to stay updated on AI and Data Engineering trends to enhance team performance and product quality. In terms of qualitative expectations, you are expected to foster a culture of innovation, continuous improvement, and excellence in software development. You should take ownership of problems, acquire necessary knowledge, and demonstrate the ability to work efficiently in an environment with loosely defined tasks and competing priorities. Collaboration with various teams within the organization, including Engineering/Research, Sales, Product, and Marketing, is essential. Effective verbal and written communication skills, as well as technical presentation abilities, are key requirements. A self-starter mindset with a passion for growth, enthusiasm for continuous learning, and the ability to share findings across the team are highly valued qualities. The ideal candidate should have experience working in AI/ML for over 10 years, preferably with vector databases, and possess a PhD or master's degree in computer science, Artificial Intelligence, or related disciplines. Knowledge of libraries such as PyTorch and transformers, quantization, model deployment, and fine-tuning LLM using PyTorch is preferred for this role.,

As a Senior Machine Learning Engineer, you will have the exciting opportunity to be involved in designing, developing, and deploying cutting-edge models for end-to-end content generation. This includes working on AI-driven image/video generation, lip syncing, and multimodal AI systems. You will be at the forefront of the latest advancements in deep generative modeling, striving to create highly realistic and controllable AI-generated media. Your responsibilities will encompass researching and developing state-of-the-art generative models like Diffusion Models, 3D VAEs, and GANs for AI-powered media synthesis. You will focus on building and optimizing AI pipelines for high-fidelity image/video generation and lip syncing. Additionally, you will be tasked with developing advanced lip-syncing and multimodal generation models that integrate speech, video, and facial animation for hyper-realistic AI-driven content. Implementing and optimizing models for real-time content generation and interactive AI applications using efficient model architectures and acceleration techniques will also be part of your role. Collaboration with software engineers to deploy models efficiently on cloud-based architectures (AWS, GCP, or Azure) will be crucial. Staying updated with the latest trends in deep generative models, diffusion models, and transformer-based vision systems to enhance AI-generated content quality will be an essential aspect of the role. Furthermore, designing and conducting experiments to evaluate model performance, improve fidelity, realism, and computational efficiency, as well as refining model architectures will be expected. Active participation in code reviews, improving model efficiency, and documenting research findings to enhance team knowledge-sharing and product development will also be part of your responsibilities. To qualify for this role, you should hold a Bachelor's or Master's degree in Computer Science, Machine Learning, or a related field. You should have a minimum of 3 years of experience working with deep generative models, such as Diffusion Models, 3D VAEs, GANs, and autoregressive models. Proficiency in Python and deep learning frameworks like PyTorch is essential. Expertise in multi-modal AI, text-to-image, and image-to-video generation, as well as audio to lip sync, is required. A strong understanding of machine learning principles and statistical methods is necessary. It would be beneficial 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 are qualities that would be valued. Familiarity with generative adversarial techniques, reinforcement learning for generative models, and large-scale AI model training will also be beneficial. Preferred qualifications include experience with transformers and vision-language models (e.g., CLIP, BLIP, GPT-4V), a background in text-to-video generation, lip-sync generation, and real-time synthetic media applications, as well as 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 would be advantageous.,

Company Size Large-scale / Global Experience Required 3 - 5 years Working Days 6 days/week Office Location Viman Nagar, Pune Role & Responsibilities Agentic AI Development: Design and develop multi-agent conversational frameworks with adaptive decision-making capabilities. Integrate goal-oriented reasoning and memory components into agents using transformer-based architectures. Build negotiation-capable bots with real-time context adaptation and recursive feedback processing. Generative AI & Model Optimization: Fine-t une LLMs/SLMs using proprietary and domain-specific datasets (NBFC, Financial Services, etc.). Apply distillation and quantization for efficient deployment on edge devices. Benchmark LLM/SLM performance on server vs. edge environments for real-time use cases. Speech And Conversational Intelligence: Implement contextual dialogue flows using speech inputs with emotion and intent tracking. Evaluate and deploy advanced Speech-to-Speech (S2S) models for naturalistic voice responses. Work on real-time speaker diarization and multi-turn, multi-party conversation tracking. Voice Biometrics & AI Security: Train and evaluate voice biometric models for secure identity verification. Implement anti-spoofing layers to detect deepfakes, replay attacks, and signal tampering. Ensure compliance with voice data privacy and ethical AI guidelines. Self-Learning & Autonomous Adaptation: Develop frameworks for agents to self-correct and adapt using feedback loops without full retraining. Enable low-footprint learning systems on-device to support personalization on the edge. Ideal Candidate Educational Qualifications: Bachelor’s/Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Experience Required: 3–5 years of experience, with a mix of core software development and AI/ML model engineering. Proven hands-on work with Conversational AI, Generative AI, or Multi-Agent Systems. Technical Proficiency: Strong programming in Python, TensorFlow/PyTorch, and model APIs (Hugging Face, LangChain, OpenAI, etc.). Expertise in STT, TTS, S2S, speaker diarization, and speech emotion recognition. LLM fine-tuning, model optimization (quantization, distillation), RAG pipelines. Understanding of agentic frameworks, cognitive architectures, or belief-desire-intention (BDI) models. Familiarity with Edge AI deployment, low-latency model serving, and privacy-compliant data pipelines. Desirable: Exposure to agent-based simulation, reinforcement learning, or behavioralmodeling. Publications, patents, or open-source contributions in conversational AI or GenAI systems. Perks, Benefits and Work Culture Our people define our passion and our audacious, incredibly rewarding achievements. Bajaj Finance Limited is one of India’s most diversified Non-banking financial companies, and among Asia’s top 10 Large workplaces. If you have the drive to get ahead, we can help find you an opportunity at any of the 500+ locations we’re present in India. Skills: edge ai deployment,adaptation,speech emotion recognition,llm fine-tuning,tensorflow,models,intelligence,model optimization,speech,speech-to-speech,data,openai,hugging face,llm,optimization,agents,langchain,pytorch,python

Job Description – AI Developer (Agentic AI Frameworks, Computer Vision & LLMs) Location (Hybrid - Bangalore) About the Role We’re seeking an AI Developer who specializes in agentic AI frameworks —LangChain, LangGraph, CrewAI, or equivalents—and who can take both vision and language models from prototype to production. You will lead the design of multi‑agent systems that coordinate perception (image classification & extraction), reasoning, and action, while owning the end‑to‑end deep‑learning life‑cycle (training, scaling, deployment, and monitoring). Key Responsibilities Scope What You’ll Do Agentic AI Frameworks (Primary Focus) Architect and implement multi‑agent workflows using LangChain, LangGraph, CrewAI, or similar. Design role hierarchies, state graphs, and tool integrations that enable autonomous data processing, decision‑making, and orchestration. Benchmark and optimize agent performance (cost, latency, reliability). Image Classification & Extraction Build and fine‑tune CNN/ViT models for classification, detection, OCR, and structured data extraction. Create scalable data‑ingestion, labeling, and augmentation pipelines. LLM Fine‑Tuning & Retrieval‑Augmented Generation (RAG) Fine‑tune open‑weight LLMs with LoRA/QLoRA, PEFT; perform SFT, DPO, or RLHF as needed. Implement RAG pipelines using vector databases (FAISS, Weaviate, pgvector) and domain‑specific adapters. Deep Learning at Scale Develop reproducible training workflows in PyTorch/TensorFlow with experiment tracking (MLflow, W&B). Serve models via TorchServe/Triton/KServe on Kubernetes, SageMaker, or GCP Vertex AI. MLOps & Production Excellence Build robust APIs/micro‑services (FastAPI, gRPC). Establish CI/CD, monitoring (Prometheus, Grafana), and automated retraining triggers. Optimize inference on CPU/GPU/Edge with ONNX/TensorRT, quantization, and pruning. Collaboration & Mentorship Translate product requirements into scalable AI services. Mentor junior engineers, conduct code and experiment reviews, and evangelize best practices. Minimum Qualifications B.S./M.S. in Computer Science, Electrical Engineering, Applied Math, or related discipline. 5+ years building production ML/DL systems with strong Python & Git . Demonstrable expertise in at least one agentic AI framework (LangChain, LangGraph, CrewAI, or comparable). Proven delivery of computer‑vision models for image classification/extraction. Hands‑on experience fine‑tuning LLMs and deploying RAG solutions. Solid understanding of containerization (Docker) and cloud AI stacks (AWS/Azure). Knowledge of distributed training, GPU acceleration, and performance optimization. ---------------------------------------------------------------------------------------------------------------------------------------------------------- Job Type: Full-time Pay: Up to ₹1,200,000.00 per year Experience: AI, LLM, RAG: 4 years (Preferred) Vector database, Image classification: 4 years (Preferred) containerization (Docker): 3 years (Preferred) ML/DL systems with strong Python & Git: 3 years (Preferred) LangChain, LangGraph, CrewAI: 3 years (Preferred) Location: Bangalore, Karnataka (Preferred) Work Location: In person

Job Description: We are seeking a highly skilled and experienced C++ Engineer to join our team. The primary responsibility will be converting existing Python-based computer vision and deep learning (CVDL) code into optimized, production-ready C++ code. The ideal candidate should be proficient in working with C++ frameworks and libraries, including TensorFlow, PyTorch, ONNX, MNN, NCNN, TensorFlow Lite (TFLite), MMDeploy, etc. The resulting C++ code will be used across Windows and Ubuntu environments, with a strong emphasis on cross-platform compatibility and performance optimization. Key Responsibilities: Convert Python-based CVDL (Computer Vision and Deep Learning) pipelines into optimized C++ implementations. Implement models and algorithms using C++ frameworks such as TensorFlow, PyTorch, ONNX, MNN, NCNN, TensorFlow Lite (TFLite), MMDeploy, and other relevant libraries. Optimize code for performance, ensuring efficient use of resources, especially in real-time processing pipelines. Ensure cross-platform compatibility, building C++ code that works seamlessly on both Windows and Ubuntu using CMakeLists. Debug, profile, and optimize deep learning inference pipelines, addressing issues related to memory usage, speed, and accuracy. Collaborate with AI teams to understand the Python codebase, gather requirements, and ensure the successful porting of features. Maintain up-to-date knowledge of the latest developments in C++ frameworks, deep learning inference engines, and performance optimization techniques. Requirements: Experience: - 5+ years of experience in C++ software development, specifically in converting Python code into C++. - 3 + years of experience with computer vision and deep learning frameworks such as TensorFlow, PyTorch, ONNX, MNN, NCNN, TensorFlow Lite (TFLite), MMDeploy , Mediapipe and Bazel build system. - Solid experience in cross-platform development for both Windows and Ubuntu using CMakeLists. Programming Skills: - Proficiency in C++ (C++11/14/17) with a deep understanding of memory management, multi-threading, and performance optimization. - Familiarity with Python, specifically in computer vision and deep learning applications, to interpret and convert code accurately. - Strong knowledge of CMake for building cross-platform applications. Technical Expertise: - Experience working with deep learning models and converting models between different formats (e.g., TensorFlow to ONNX, PyTorch to NCNN, etc.). - Experience with OpenCV and other related computer vision libraries. - Understanding of inference optimizations such as quantization, pruning, and model acceleration will be plus. Communication: - Strong problem-solving skills and the ability to work in a collaborative, fast-paced environment. - Ability to communicate effectively with cross-functional teams, including data scientists, ML engineers, and Python developers.

About the Role We are seeking a visionary and technically astute Lead AI Architect to lead the architecture and design of scalable AI systems and next-generation intelligent platforms. As a core member of the leadership team, you will be responsible for driving end-to-end architectural strategy, model optimization, and AI infrastructure that powers mission-critical solutions across our product lines. This is a foundational role for someone passionate about architecting solutions involving RAG , SLMs/LLMs , multi-agent systems , and scalable model pipelines across cloud-native environments. Salary 30 - 45 LPA with additional benefits. Key Responsibilities Define and own the AI/ML architectural roadmap , aligning with product vision and technical goals. Architect and oversee implementation of RAG-based solutions , LLM/SLM fine-tuning pipelines , and multi-agent orchestration . Lead design of model training and inference pipelines ensuring scalability, modularity, and observability. Evaluate and select open-source and proprietary foundation models for fine-tuning, instruction tuning, and domain adaptation. Guide integration of vector databases, semantic search, and prompt orchestration frameworks (LangChain, LlamaIndex, etc.). Ensure best practices in model deployment, versioning, monitoring , and performance optimization (GPU utilization, memory efficiency, etc.). Collaborate with Engineering, DevOps, Product, and Data Science teams to bring AI features to production. Mentor mid-level engineers and interns; contribute to technical leadership and code quality . Maintain awareness of latest research, model capabilities, and trends in AI. Required Skills & Qualifications 6+ years of hands-on experience in AI/ML architecture and model deployment. Expert-level knowledge of Python and libraries such as PyTorch, Hugging Face Transformers, scikit-learn, and FastAPI. Deep understanding of LLMs/SLMs, embedding models, tokenization strategies, fine-tuning, quantization, and LoRA/QLoRA. Proven experience with Retrieval-Augmented Generation (RAG) pipelines and vector DBs like FAISS, Pinecone, or Weaviate. Strong grasp of system design, distributed training, MLOps, and scalable cloud-based infrastructure (AWS/GCP/Azure). Experience with containerization (Docker), orchestration (Kubernetes), and experiment tracking (MLFlow, W&B). Experience in building secure and performant REST APIs , deploying and monitoring AI services in production. Nice to Have Exposure to multi-agent frameworks, task planners, or LangGraph. Experience leading AI platform teams or architecting enterprise-scale ML platforms. Familiarity with Data Governance, Responsible AI, and model compliance requirements. Published papers, open-source contributions, or patents in the AI/ML domain. Why Join Us Be at the forefront of innovation in AI and language intelligence. Influence strategic technical decisions and drive company-wide AI architecture. Lead a growing AI team in a high-impact, fast-paced environment. Competitive compensation, equity options, and leadership opportunity.

About the job Location: Bangalore Career Level: IC3 Oracle Cloud Infrastructure (OCI) is at the forefront of cloud innovation, blending the agility of a startup with the reliability of a leading enterprise software provider. Our AI Science team pioneers state-of-the-art machine learning solutions that empower customers and solve complex real-world problems at scale. We’re looking for an experienced Sr. Applied Science (IC3) with deep hand-on experience in Generative AI and Computer Vision area to develop highly complex and accurate data science model. In this role, you will develop of secure, scalable, and innovative AI solutions leveraging cutting-edge techniques in computer vision, Large multimodal models and other GenAI technologies. As a Senior Applied Scientist, you will develop and deploy state-of-the-art computer vision solutions leveraging generative AI technologies such as Large multimodal models and computer vision technologies such as image classification, object detection, vision grounding etc. This individual contributor(IC) role will build best-in-class computer vision solutions at scale. is perfect for a hands-on data science architecture design and is eager to drive innovation and excellence in AI and computer vision area. You will partner with the Product and Engineering managers to influence strategic decisions, drive experimentation and communicate results to higher managements. You will build best-in-class LLM/LMM/computer vision solutions for the Oracle business domain at scale. You will also partner with Product Management, Data Labelling and Engineering teams to get to develop build best-in-class computer vision solutions at scale. The ideal candidate has extensive experience with computer vision techniques, deep learning techniques, model serving, and a demonstrated ability to think strategicallyabout business, product, and technical challenges to contribute to the development of current and future vision services. Key Responsibilities Development of advanced AI models and algorithms, focusing on large language model, large multimodal, computer vision and foundation models. Design, implement and test the critical module/features of AI service that are correct, highly available, scalable, and cost-effective. Champion best practices for testing, benchmarking, and model validation to ensure reliability and performance. Analysis of ML models, and optimizing models for accuracy and latency. Large-scale training & production deployment with ML models. Own data analysis, feature engineering, technique selection & implementation, debugging, and maintenance of production model. Experience implementing machine learning algorithms or research papers from scratch to production. Work with large, complex data sets. Proactively identify the technical issues/bugs and provide innovative solutions. File patent and publication as by product of solving complex business problems Partner closely with product managers, engineering leads, and annotation/data teams to define requirements, data quality assurance and acceptance of data/annotation as required. Leverage Oracle Cloud technology. Preferred Qualifications Ph.D. (preferred) or Master’s in Computer Science, Machine Learning, Computer Vision, or related field. PhD in computer vision or 2+ years of Experience designing, implementing and deploying computer vision models in production environments Expertise in GenAI, LLMs, LMMs, object detection, facial recognition, and image classification. Strong foundation in deep learning architectures such as CNNs, transformers, diffusion models, and multimodal models. Expert in at least one high level language such as Python/Java/C++ Practical experience in ML algorithm design, model training and production deployment using microservices architecture Practical experience working in a cloud environment: Oracle Cloud (OCI), AWS, GCP, Azure or similar technology. Experience or willingness to learn and work in Agile and iterative development processes. Strong drive to learn and master new technologies and techniques. Deep understanding of data structures, algorithms, and excellent problem-solving skills. You enjoy a fast-paced work environment. Identify data science use cases and design scalable solutions that can be built as a feature of the product/service. Contributes to writing production model code. Work with Software Engineering teams to deploy them in production. Set up environment needed to run experiments for all projects. Set up distributed environments. Design and implement algorithms, train models, and deploy both to production to validate premises and achieve goals. Design and execute offline/online experiments and model performance testing. Work with large, complex data sets. Solve difficult, non-routine analysis problems, applying advanced analytical methods as needed. Address business/customer problems and questions using statistical and machine learning techniques to achieve business goals and KPI's. Come up with innovative solutions to address tradeoffs or challenges faced by team. Stay up-to date with research and trends regarding latest algorithms in ML or other industry/domain space. Perform research in emerging areas, which may include efficient neural network development including quantization, pruning, compression and neural architecture search, as well as novel differentiable compute primitives. May perform other duties as assigned.

Applied Machine Learning Scientist – Voice AI, NLP & GenAI Applications Location : Sector 63, Gurugram, Haryana – 100% In-Office Working Days : Monday to Friday, with 2nd and 4th Saturdays off Working Hours : 10:30 AM – 8:00 PM Experience : 3–7 years in applied ML, with at least 2 years focused on voice, NLP, or GenAI deployments Function : AI/ML Research & Engineering | Conversational Intelligence | Real-time Model Deployment Apply : careers@darwix.ai Subject Line : “Application – Applied ML Scientist – [Your Name]” About Darwix AI Darwix AI is a GenAI-powered platform transforming how enterprise sales, support, and credit teams engage with customers. Our proprietary AI stack ingests data across calls, chat, email, and CCTV streams to generate: Real-time nudges for agents and reps Conversational analytics and scoring to drive performance CCTV-based behavior insights to boost in-store conversion We’re live across leading enterprises in India and MENA, including IndiaMart, Wakefit, Emaar, GIVA, Bank Dofar , and others. We’re backed by top-tier operators and venture investors and scaling rapidly across multiple verticals and geographies. Role Overview We are looking for a hands-on, impact-driven Applied Machine Learning Scientist to build, optimize, and productionize AI models across ASR, NLP, and LLM-driven intelligence layers . This is a core role in our AI/ML team where you’ll be responsible for building the foundational ML capabilities that drive our real-time sales intelligence platform. You will work on large-scale multilingual voice-to-text pipelines, transformer-based intent detection, and retrieval-augmented generation systems used in live enterprise deployments. Key ResponsibilitiesVoice-to-Text (ASR) Engineering Deploy and fine-tune ASR models such as WhisperX, wav2vec 2.0, or DeepSpeech for Indian and GCC languages Integrate diarization and punctuation recovery pipelines Benchmark and improve transcription accuracy across noisy call environments Optimize ASR latency for real-time and batch processing modes NLP & Conversational Intelligence Train and deploy NLP models for sentence classification, intent tagging, sentiment, emotion, and behavioral scoring Build call scoring logic aligned to domain-specific taxonomies (sales pitch, empathy, CTA, etc.) Fine-tune transformers (BERT, RoBERTa, etc.) for multilingual performance Contribute to real-time inference APIs for NLP outputs in live dashboards GenAI & LLM Systems Design and test GenAI prompts for summarization, coaching, and feedback generation Integrate retrieval-augmented generation (RAG) using OpenAI, HuggingFace, or open-source LLMs Collaborate with product and engineering teams to deliver LLM-based features with measurable accuracy and latency metrics Implement prompt tuning, caching, and fallback strategies to ensure system reliability Experimentation & Deployment Own model lifecycle: data preparation, training, evaluation, deployment, monitoring Build reproducible training pipelines using MLflow, DVC, or similar tools Write efficient, well-structured, production-ready code for inference APIs Document experiments and share insights with cross-functional teams Required Qualifications Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or related fields 3–7 years experience applying ML in production, including NLP and/or speech Experience with transformer-based architectures for text or audio (e.g., BERT, Wav2Vec, Whisper) Strong Python skills with experience in PyTorch or TensorFlow Experience with REST APIs, model packaging (FastAPI, Flask, etc.), and containerization (Docker) Familiarity with audio pre-processing, signal enhancement, or feature extraction (MFCC, spectrograms) Knowledge of MLOps tools for experiment tracking, monitoring, and reproducibility Ability to work collaboratively in a fast-paced startup environment Preferred Skills Prior experience working with multilingual datasets (Hindi, Arabic, Tamil, etc.) Knowledge of diarization and speaker separation algorithms Experience with LLM APIs (OpenAI, Cohere, Mistral, LLaMA) and RAG pipelines Familiarity with inference optimization techniques (quantization, ONNX, TorchScript) Contribution to open-source ASR or NLP projects Working knowledge of AWS/GCP/Azure cloud platforms What Success Looks Like Transcription accuracy improvement ≥ 85% across core languages NLP pipelines used in ≥ 80% of Darwix AI’s daily analyzed calls 3–5 LLM-driven product features delivered in the first year Inference latency reduced by 30–50% through model and infra optimization AI features embedded across all Tier 1 customer accounts within 12 months Life at Darwix AI You will be working in a high-velocity product organization where AI is core to our value proposition. You’ll collaborate directly with the founding team and cross-functional leads, have access to enterprise datasets, and work on ML systems that impact large-scale, real-time operations. We value rigor, ownership, and speed. Model ideas become experiments in days, and successful experiments become deployed product features in weeks. Compensation & Perks Competitive fixed salary based on experience Quarterly/Annual performance-linked bonuses ESOP eligibility post 12 months Compute credits and model experimentation environment Health insurance, mental wellness stipend Premium tools and GPU access for model development Learning wallet for certifications, courses, and AI research access Career Path Year 1: Deliver production-grade ASR/NLP/LLM systems for high-usage product modules Year 2: Transition into Senior Applied Scientist or Tech Lead for conversation intelligence Year 3: Grow into Head of Applied AI or Architect-level roles across vertical product lines How to Apply Email the following to careers@darwix.ai : Updated resume (PDF) A short write-up (200 words max): “How would you design and optimize a multilingual voice-to-text and NLP pipeline for noisy call center data in Hindi and English?” Optional: GitHub or portfolio links demonstrating your work Subject Line : “Application – Applied Machine Learning Scientist – [Your Name]”

Head of AI & ML Platforms Focus : Voice AI, NLP, Conversation Intelligence for Omnichannel Enterprise Sales Location : Sector 63, Gurugram, Haryana — Full-time, 100% In-Office Work Hours : 10:30 AM – 8:00 PM, Monday to Friday (2nd and 4th Saturdays off) Experience Required : 8–15 years in AI/ML, with 3+ years leading teams in voice, NLP, or conversation platforms Apply : careers@darwix.ai Subject Line : “Application – Head of AI & ML Platforms – [Your Name]” About Darwix AI Darwix AI is a GenAI-powered platform for enterprise revenue teams across sales, support, credit, and retail. Our proprietary AI stack ingests multimodal inputs—voice calls, chat logs, emails, and CCTV streams—and delivers contextual nudges, conversation scoring, and performance analytics in real time. Our suite of products includes: Transform+ : Real-time conversational intelligence for contact centers and field sales Sherpa.ai : A multilingual GenAI assistant that provides in-the-moment coaching, summaries, and objection handling support Store Intel : A computer vision solution that transforms CCTV feeds into actionable insights for physical retail spaces Darwix AI is trusted by large enterprises such as IndiaMart, Wakefit, Emaar, GIVA, Bank Dofar, and Sobha Realty , and is backed by leading institutional and operator investors. We are expanding rapidly across India, the Middle East, and Southeast Asia. Role Overview We are seeking a highly experienced and technically strong Head of AI & ML Platforms to architect and lead the end-to-end AI systems powering our voice intelligence, NLP, and GenAI solutions. This is a leadership role that blends research depth with applied engineering execution. The ideal candidate will have deep experience in building and deploying voice-to-text pipelines, multilingual NLP systems, and production-grade inference workflows. The individual will be responsible for model design, accuracy benchmarking, latency optimization, infrastructure orchestration, and integration across our product suite. This is a critical leadership role with direct influence over product velocity, enterprise client outcomes, and future platform scalability. Key ResponsibilitiesVoice-to-Text (ASR) Architecture Lead the design and optimization of large-scale automatic speech recognition (ASR) pipelines using open-source and commercial frameworks (e.g., WhisperX, Deepgram, AWS Transcribe) Enhance speaker diarization, custom vocabulary accuracy, and latency performance for real-time streaming scenarios Build fallback ASR workflows for offline and batch mode processing Implement multilingual and domain-specific tuning, especially for Indian and GCC languages Natural Language Processing and Conversation Analysis Build NLP models for conversation segmentation, intent detection, tone/sentiment analysis, and call scoring Implement multilingual support (Hindi, Arabic, Tamil, etc.) with fallback strategies for mixed-language and dialectal inputs Develop robust algorithms for real-time classification of sales behaviors (e.g., probing, pitching, objection handling) Train and fine-tune transformer-based models (e.g., BERT, RoBERTa, DeBERTa) and sentence embedding models for text analytics GenAI and LLM Integration Design modular GenAI pipelines for nudging, summarization, and response generation using tools like LangChain, LlamaIndex, and OpenAI APIs Implement retrieval-augmented generation (RAG) architectures for contextual, accurate, and hallucination-resistant outputs Build prompt orchestration frameworks that support real-time sales coaching across channels Ensure safety, reliability, and performance of LLM-driven outputs across use cases Infrastructure and Deployment Lead the development of scalable, secure, and low-latency AI services deployed via FastAPI, TorchServe, or similar frameworks Oversee model versioning, monitoring, and retraining workflows using MLflow, DVC, or other MLOps tools Build hybrid inference systems for batch, real-time, and edge scenarios depending on product usage Optimize inference pipelines for GPU/CPU balance, resource scheduling, and runtime efficiency Team Leadership and Cross-functional Collaboration Recruit, manage, and mentor a team of machine learning engineers and research scientists Collaborate closely with Product, Engineering, and Customer Success to translate product requirements into AI features Own AI roadmap planning, sprint delivery, and KPI measurement Serve as the subject-matter expert for AI-related client discussions, sales demos, and enterprise implementation roadmaps Required Qualifications 8+ years of experience in AI/ML with a minimum of 3 years in voice AI, NLP, or conversational platforms Proven experience delivering production-grade ASR or NLP systems at scale Deep familiarity with Python, PyTorch, HuggingFace, FastAPI, and containerized environments (Docker/Kubernetes) Expertise in fine-tuning LLMs and building multi-language, multi-modal intelligence stacks Demonstrated experience with tools such as WhisperX, Deepgram, Azure Speech, LangChain, MLflow, or Triton Inference Server Experience deploying real-time or near real-time inference models at enterprise scale Strong architectural thinking with the ability to design modular, reusable, and scalable ML services Track record of building and leading high-performing ML teams Preferred Skills Background in telecom, contact center AI, conversational analytics, or field sales optimization Familiarity with GPU deployment, model quantization, and inference optimization Experience with low-resource languages and multilingual data augmentation Understanding of sales enablement workflows and domain-specific ontology development Experience integrating AI models into customer-facing SaaS dashboards and APIs Success Metrics Transcription accuracy improvement by ≥15% across core languages within 6 months End-to-end voice-to-nudge latency reduced below 5 seconds GenAI assistant adoption across 70%+ of eligible conversations AI-driven call scoring rolled out across 100% of Tier 1 clients within 9 months Model deployment velocity (dev to prod) reduced by ≥40% through tooling and process improvements Culture at Darwix AI At Darwix AI, we operate at the intersection of engineering velocity and product clarity. We move fast, prioritize outcomes over optics, and expect leaders to drive hands-on impact. You will work directly with the founding team and senior leaders across engineering, product, and GTM functions. Expect ownership, direct communication, and a culture that values builders who scale systems, people, and strategy. Compensation and Benefits Competitive fixed compensation Performance-based bonuses and growth-linked incentives ESOP eligibility for leadership candidates Access to GPU/compute credits and model experimentation infrastructure Comprehensive medical insurance and wellness programs Dedicated learning and development budget for technical and leadership upskilling MacBook Pro, premium workstation, and access to industry tooling licenses Career Progression 12-month roadmap: Build and stabilize AI platform across all product lines 18–24-month horizon: Elevate to VP of AI or Chief AI Officer as platform scale increases globally Future leadership role in enabling new verticals (e.g., healthcare, finance, logistics) with domain-specific GenAI solutions How to Apply Send the following to careers@darwix.ai : Updated CV (PDF format) A short statement (200 words max) on: “How would you design a multilingual voice-to-text pipeline optimized for low-resource Indic languages, with real-time nudge delivery?” Links to any relevant GitHub repos, publications, or deployed projects (optional) Subject Line : “Application – Head of AI & ML Platforms – [Your Name]”

Job Description About the job Location: Bangalore Career Level: IC3 Oracle Cloud Infrastructure (OCI) is at the forefront of cloud innovation, blending the agility of a startup with the reliability of a leading enterprise software provider. Our AI Science team pioneers state-of-the-art machine learning solutions that empower customers and solve complex real-world problems at scale. We’re looking for an experienced Sr. Applied Science (IC3) with deep hand-on experience in Generative AI and Computer Vision area to develop highly complex and accurate data science model. In this role, you will develop of secure, scalable, and innovative AI solutions leveraging cutting-edge techniques in computer vision, Large multimodal models and other GenAI technologies. As a Senior Applied Scientist, you will develop and deploy state-of-the-art computer vision solutions leveraging generative AI technologies such as Large multimodal models and computer vision technologies such as image classification, object detection, vision grounding etc. This individual contributor(IC) role will build best-in-class computer vision solutions at scale. is perfect for a hands-on data science architecture design and is eager to drive innovation and excellence in AI and computer vision area. You will partner with the Product and Engineering managers to influence strategic decisions, drive experimentation and communicate results to higher managements. You will build best-in-class LLM/LMM/computer vision solutions for the Oracle business domain at scale. You will also partner with Product Management, Data Labelling and Engineering teams to get to develop build best-in-class computer vision solutions at scale. The ideal candidate has extensive experience with computer vision techniques, deep learning techniques, model serving, and a demonstrated ability to think strategicallyabout business, product, and technical challenges to contribute to the development of current and future vision services. Key Responsibilities Development of advanced AI models and algorithms, focusing on large language model, large multimodal, computer vision and foundation models. Design, implement and test the critical module/features of AI service that are correct, highly available, scalable, and cost-effective. Champion best practices for testing, benchmarking, and model validation to ensure reliability and performance. Analysis of ML models, and optimizing models for accuracy and latency. Large-scale training & production deployment with ML models. Own data analysis, feature engineering, technique selection & implementation, debugging, and maintenance of production model. Experience implementing machine learning algorithms or research papers from scratch to production. Work with large, complex data sets. Proactively identify the technical issues/bugs and provide innovative solutions. File patent and publication as by product of solving complex business problems Partner closely with product managers, engineering leads, and annotation/data teams to define requirements, data quality assurance and acceptance of data/annotation as required. Leverage Oracle Cloud technology. Preferred Qualifications Ph.D. (preferred) or Master’s in Computer Science, Machine Learning, Computer Vision, or related field. PhD in computer vision or 2+ years of Experience designing, implementing and deploying computer vision models in production environments Expertise in GenAI, LLMs, LMMs, object detection, facial recognition, and image classification. Strong foundation indeep learning architectures such as CNNs, transformers, diffusion models, and multimodal models. Expert in at least one high level language such as Python/Java/C++ Practical experience in ML algorithm design, model training and production deployment using microservices architecture Practical experience working in a cloud environment: Oracle Cloud (OCI), AWS, GCP, Azure or similar technology. Experience or willingness to learn and work in Agile and iterative development processes. Strong drive to learn and master new technologies and techniques. Deep understanding of data structures, algorithms, and excellent problem-solving skills. You enjoy a fast-paced work environment. Responsibilities Identify data science use cases and design scalable solutions that can be built as a feature of the product/service. Contributes to writing production model code. Work with Software Engineering teams to deploy them in production. Set up environment needed to run experiments for all projects. Set up distributed environments. Design and implement algorithms, train models, and deploy both to production to validate premises and achieve goals. Design and execute offline/online experiments and model performance testing. Work with large, complex data sets. Solve difficult, non-routine analysis problems, applying advanced analytical methods as needed. Address business/customer problems and questions using statistical and machine learning techniques to achieve business goals and KPI's. Come up with innovative solutions to address tradeoffs or challenges faced by team. Stay up-to date with research and trends regarding latest algorithms in ML or other industry/domain space. Perform research in emerging areas, which may include efficient neural network development including quantization, pruning, compression and neural architecture search, as well as novel differentiable compute primitives. May perform other duties as assigned. Qualifications Career Level - IC3 About Us As a world leader in cloud solutions, Oracle uses tomorrow’s technology to tackle today’s challenges. We’ve partnered with industry-leaders in almost every sector—and continue to thrive after 40+ years of change by operating with integrity. We know that true innovation starts when everyone is empowered to contribute. That’s why we’re committed to growing an inclusive workforce that promotes opportunities for all. Oracle careers open the door to global opportunities where work-life balance flourishes. We offer competitive benefits based on parity and consistency and support our people with flexible medical, life insurance, and retirement options. We also encourage employees to give back to their communities through our volunteer programs. We’re committed to including people with disabilities at all stages of the employment process. If you require accessibility assistance or accommodation for a disability at any point, let us know by emailing accommodation-request_mb@oracle.com or by calling +1 888 404 2494 in the United States. Oracle is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans’ status, or any other characteristic protected by law. Oracle will consider for employment qualified applicants with arrest and conviction records pursuant to applicable law.