32 Ml Ops Jobs - Page 2

We are seeking a highly experienced and strategic Senior Manager Applied Science to lead and scale our applied research and machine learning initiatives. This role involves working at the intersection of cutting-edge AI/ML technologies and real-world business challenges to drive measurable impact. Key Responsibilities: Lead a team of applied scientists and machine learning engineers to develop scalable AI/ML models. Define and drive the scientific vision, strategy, and roadmap aligned with business goals. Collaborate cross-functionally with product, engineering, and analytics teams. Stay ahead of emerging technologies and apply them to solve complex business problems. Publish research, file patents, or present findings in internal/external forums as needed. Requirements: 10+ years of experience in applied science, machine learning, or data science roles. Strong background in statistics, optimization, deep learning, NLP, or related fields. Hands-on experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn. Proven experience in leading high-performance technical teams. Advanced degree (Ph.D. or Master’s) in Computer Science, Mathematics, Statistics, or a related field. Excellent communication and leadership skills. Preferred Qualifications: Experience in a product-led tech company or research lab environment. Track record of deploying ML models in production. Publications or patents in relevant areas.

Notice Period : Candidates with up to 1-month notice preferred Findability Sciences is looking for a hands-on AI expert with experience in developing and implementing comprehensive predictive and generative AI solutions. This is a core technical role rather than a support-based one. You will lead innovation and delivery across multiple industries. What we are looking for: 3+ years of experience in AI/ML with a Masters or Ph.D. in a relevant field Strong knowledge of Python, SQL, Machine Learning, LLMs, RAG, and Prompt Engineering Experience in predictive modeling, time series forecasting, and generative AI use cases Experience with ML Ops workflows model deployment, monitoring, versioning, and pipeline automation Key Responsibilities: Design and deploy predictive & GenAI solutions for real-world business use cases Build and optimize LLM-based workflows for summarization, retrieval, and Q&A Collaborate with cross-functional teams to define use cases and develop proof-of-concepts Translate business problems into ML/GenAI solutions and deliver outcomes Validate, compare, and optimize models for performance and scalability Apply basic ML Ops practices to ensure smooth deployment and monitoring of models Contribute to reusable pipelines, prompt tuning strategies, and production integration Present actionable insights and models to stakeholders clearly and effectively

Notice Period: Candidates with up to 1-month notice preferred Findability Sciences is looking for a hands-on AI expert with experience in developing and implementing comprehensive predictive and generative AI solutions. This is a core technical role rather than a support-based one. What we are looking for: 3+ years of experience in AI/ML with a Masters or Ph.D. in a relevant field Strong knowledge of Python, SQL, Machine Learning, LLMs, RAG, and Prompt Engineering Experience in predictive modeling, time series forecasting, and generative AI use cases Experience with ML Ops workflows model deployment, monitoring, versioning, and pipeline automation Key Responsibilities: Design and deploy predictive & GenAI solutions for real-world business use cases Build and optimize LLM-based workflows for summarization, retrieval, and Q&A Collaborate with cross-functional teams to define use cases and develop proof-of-concepts Translate business problems into ML/GenAI solutions and deliver outcomes Validate, compare, and optimize models for performance and scalability Apply basic ML Ops practices to ensure smooth deployment and monitoring of models Contribute to reusable pipelines, prompt tuning strategies, and production integration Present actionable insights and models to stakeholders clearly and effectively

Job description MLOps Engineer Bangalore (work at office) 5+ Years experience relevant in MLOPs Mandatory Skills: Strong proficiency in Generative AI, Large Language Models (LLMs), deep learning, agentic frameworks, and RAG setup. Experience in designing and implementing machine learning models using scikit-learn and TensorFlow. Hands-on expertise with AI/ML frameworks such as Hugging Face, LangChain, LangGraph, and PyTorch. Cloud AI services experience, particularly in AWS SageMaker and AWS Bedrock. MLOps & DevOps: Knowledge of data pipeline setup, Apache Airflow, CI/CD, and containerization (Docker, Kubernetes). API Development: Ability to develop and maintain APIs following RESTful principles. Technical proficiency in Elastic, Python, YAML, and system integrations. Nice to Have: Experience with Observability, Ansible, Terraform, Git, Microservices, AIOps, and scripting in Python. Familiarity with AI cloud services such as Azure OpenAI and Google Vertex AI.

About the role: Were building an agentic AI platform that turns one line of text and a video feed into end-to-end, real-time computer-vision solutionsthink semantic video search, object / action recognition, and task-oriented visual agents deployable with a single click. As a Gen AI ML Engineer, youll architect the core vision & multimodal-reasoning stack and pave the road from prototype to production. Roles and Responsibilities: Semantic video search Ship a pipeline that allows users to type show every forklift near aisle 5 in the last 30 minutes and get keyed-off clips in 1 s. Wire embeddings to a hybrid FAISS/HNSW index; surface results through a simple REST & React playground. Create agentic pipelines Chain vision language models and zero/few-shot vision models with LLM planners (Gemini, GPT-4o, AutoGen, etc.) so a single prompt becomes a multi-step perception workflow. Profile and accelerate inference (TensorRT, ONNX, quantization, batching) to meet latency / throughput targets on GPU and CPU fleets. Rapid prototyping loops Run weekly paper-to-prototype spikes: reproduce a fresh arXiv idea, benchmark, and decide go/no-go in 5 days. Hand successful python scripts & checkpoints to MLOps for productionizationno plumbing marathons. Data & Evaluation Spin up scalable pipelines for video ingestion, labeling (active learning, weak supervision), experiment tracking, and continuous evaluation. Collaborate & Lead Partner with product and ML Ops engineers; set research direction, mentor future hires, and establish best practices. Must-have skill set: 13 years deep-learning research experience (internships & grad work count). Fluency in Python + PyTorch; comfortable hacking large vision/LLM repos. Proof you ship ideasfirst-author paper, OSS repo, Kaggle medal, or faithful reproduction of a cutting-edge model. Hands-on with LLM prompting/fine-tuning and at least one agent framework. Able to turn fuzzy product asks into measurable experiments and explain results clearly. Bonus cred: Large-scale video retrieval or temporal grounding experience. Prior work building agentic-AI pipelines that combine perception models with LLM reasoning. Open-source contributions to GenAI/vision libs (OpenCLIP, Vid2Seq, ViperGPT, etc.). What can you expect? Ability to shape the future of manufacturing by leveraging best-in-class AI and software; we are a unique organization with niche skill set that you would also develop while working with us World class work culture, coaching and development Mentoring from highly experienced leadership from world class companies (refer to Ripik.AI website for details) International exposure

AI Engineer Enterprise Agent Development Experience: 3 - 5 Years Exp Salary : INR 16-20 Lacs per annum Preferred Notice Period : Within 30 Days Shift : 3:00PM to 12:00AM IST Opportunity Type: Remote Placement Type: Permanent (*Note: This is a requirement for one of Uplers' Clients) Must have skills required : LangChain, LLM, ML Ops, AWS, Docker, Python Good to have skills : open-source, Palantir, privacy techniques, rag, Snowflake B2B SaaS (One of Uplers' Clients) is Looking for: AI Engineer Enterprise Agent Development who is passionate about their work, eager to learn and grow, and who is committed to delivering exceptional results. If you are a team player, with a positive attitude and a desire to make a difference, then we want to hear from you. Role Overview Description Join the Team Revolutionizing Procurement Analytics at SenseCloud Imagine working at a company where you get the best of all worlds: the fast-paced execution of a startup and the guidance of leaders whove built things that actually work at scale. Were not just rethinking how procurement analytics is done were redefining them. At Sensecloud, we envision a future where Procurement data management and analytics is as intuitive as your favorite app. No more complex spreadsheets, no more waiting in line to get IT and analytics teams attention, no more clunky dashboards just real-time insights, smooth automation, and a frictionless experience that helps companies make fast decisions. If youre ready to help us build the future of procurement analytics, come join the ride. You'll work alongside the brightest minds in the industry, learn cutting-edge technologies, and be empowered to take on challenges that will stretch your skills and your thinking. If youre ready to help us build the future of procurement, analytics come join the ride. About the Role Were looking for an AI Engineer who can design, implement, and productionize LLM-powered agents that solve real-world enterprise problemsthink automated research assistants, data-driven copilots, and workflow optimizers. Youll own projects end-to-end: scoping, prototyping, evaluating, and deploying scalable agent pipelines that integrate seamlessly with our customers ecosystems. What you'll do: Architect & build multi-agent systems using frameworks such as LangChain, LangGraph, AutoGen, Google ADK, Palantir Foundry, or custom orchestration layers. Fine-tune and prompt-engineer LLMs (OpenAI, Anthropic, open-source) for retrieval-augmented generation (RAG), reasoning, and tool use. Integrate agents with enterprise data sources (APIs, SQL/NoSQL DBs, vector stores like Pinecone, Elasticsearch) and downstream applications (Snowflake, ServiceNow, custom APIs). Own the MLOps lifecycle: containerize (Docker), automate CI/CD, monitor drift & hallucinations, set up guardrails, observability, and rollback strategies. Collaborate cross-functionally with product, UX, and customer teams to translate requirements into robust agent capabilities and user-facing features. Benchmark & iterate on latency, cost, and accuracy; design experiments, run A/B tests, and present findings to stakeholders. Stay current with the rapidly evolving GenAI landscape and champion best practices in ethical AI, data privacy, and security. Must-Have Technical Skills 35 years software engineering or ML experience in production environments. Strong Python skills (async I/O, typing, testing) plus familiarity with TypeScript/Node or Go a bonus. Hands-on with at least one LLM/agent frameworks and platforms (LangChain, LangGraph, Google ADK, LlamaIndex, Emma, etc.). Solid grasp of vector databases (Pinecone, Weaviate, FAISS) and embedding models. Experience building and securing REST/GraphQL APIs and microservices. Cloud skills on AWS, Azure, or GCP (serverless, IAM, networking, cost optimization). Proficient with Git, Docker, CI/CD (GitHub Actions, GitLab CI, or similar). Knowledge of ML Ops tooling (Kubeflow, MLflow, SageMaker, Vertex AI) or equivalent custom pipelines. Core Soft Skills Product mindset: translate ambiguous requirements into clear deliverables and user value. Communication: explain complex AI concepts to both engineers and executives; write crisp documentation. Collaboration & ownership: thrive in cross-disciplinary teams, proactively unblock yourself and others. Bias for action: experiment quickly, measure, iteratewithout sacrificing quality or security. Growth attitude: stay curious, seek feedback, mentor juniors, and adapt to the fast-moving GenAI space. Nice-to-Haves Experience with RAG pipelines over enterprise knowledge bases (SharePoint, Confluence, Snowflake). Hands-on with MCP servers/clients, MCP Toolbox for Databases, or similar gateway patterns. Familiarity with LLM evaluation frameworks (LangSmith, TruLens, Ragas). Familiarity with Palantir/Foundry. Knowledge of privacy-enhancing techniques (data anonymization, differential privacy). Prior work on conversational UX, prompt marketplaces, or agent simulators. Contributions to open-source AI projects or published research. Why Join Us? Direct impact on products used by Fortune 500 teams. Work with cutting-edge models and shape best practices for enterprise AI agents. Collaborative culture that values experimentation, continuous learning, and worklife balance. Competitive salary, equity, remote-first flexibility, and professional development budget. How to apply for this opportunity: Easy 3-Step Process: 1. Click On Apply! And Register or log in on our portal 2. Upload updated Resume & Complete the Screening Form 3. Increase your chances to get shortlisted & meet the client for the Interview! About Our Client: SenseCloud.ai is a procurement-focused data and AI company that offers a self-service analytics platform designed to simplify complex procurement processes. Their business model centers on providing intuitive, AI-driven tools that empower procurement professionals to derive insights without the need for IT or data science expertise. About Uplers: Our goal is to make hiring and getting hired reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant product and engineering job opportunities and progress in their career. (Note: There are many more opportunities apart from this on the portal.) So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Exp - 6- 10 Years Level - Senior Consultant Skill - ML OPS with Gen AI Location - Bengaluru Event on 9th May in Bangalore location Hybrid Mode (2 days WFO in a week) Education - B.Tech/B.E/MS/MBA ML OPs Engineer Required: 6-10 years of Consulting, Data, and Analytics experience Experience in descriptive & predictive analytics, both theoretical and practical knowledge in basic ML algorithms like linear and non-linear regression, linear and non-linear classification, dimensional reduction, anomaly detection, statistical concepts and techniques like theoretical distributions, parametric and non-parametric inference 6+ years of experience implementing & executing data science projects throughout the entire lifecycle: Developing/designing and implementing solutions E2E in production. Strong knowledge of Python or R Programming experience with Node.js, SQL, Java, JavaScript OR PERL Experience in cloud-based data platforms on AWS, GCP and Azure Understanding of multi-tier application architectures Ability to develop, test and maintain programming environments and architectural standards Foundational understanding of application development lifecycle and using tools like ANT, Maven, Gradle and Version control (SVN OR GIT OR BitBucket) Experience with working in an agile development lifecycle and continuous integration processes using tools such as Jenkins Experience in doing deployments for Java, .NET , Angular , Node.js , PHP, Python applications using Jenkins/Bamboo Experience on code quality assessment tools and integration with CI tool Strong logical structuring and problem-solving skills Strong verbal, written and presentation skills Preferred Additional Experience in using Spark either with Scala or Python Experience with different database types like RDS and NoSQL Experience in cloud deployments Knowledge of working in a Linux environment Strong understanding and experience configuring, managing and supporting applications using tools such as OpsWorks, Datadog and CloudWatch on AWS Experience in Docker /Swarm / Kubernetes Experience or exposure to Test Driven Development Experience (Junit / TestNG) Experience on Behavior Driven Development Experience (Cucumber / Selenium) Expertise in any commercial data visualization tool such as Tableau, Qlik, Power BI Experience with real time data movement solutions that use security and encryption protocols while data is in transit