Senior Analyst - Data Science

LatentView Analytics · Remote

Source and collection record

Last observed by our collector: 8 October 2026 at 11:39 pm IST. This is not a manual review or a confirmation from the employer.

Job type and experience labels are automated discovery categories. The employer determines eligibility. Original experience wording was not retained separately; check the current employer page.

How sourcing and classification work · Report a discrepancy

Your application evidence checklist

Mark the statements you can support after reading the employer source. This checklist stays on this page; it does not score your eligibility or submit an application.

Attendance and availability: I checked the employer page for work location, office attendance, start date and duration.Current requisition: I checked the current employer requisition and its application requirements.

0 of 2 checks marked. Keep unresolved requirements as questions for the employer.

Collected role description

<div>Role Summary</div><div> </div><div>We are looking for a Senior Data / ML Engineer with 6+ years of experience to design, build, and productionize GenAI, LLM, RAG, and agentic AI solutions. The role is highly hands-on and focused on developing scalable, reliable, and enterprise-ready AI systems that solve real-world business problems.</div><div> </div><div>Roles & Responsibilities</div><div> </div><ul><li>Design and develop LLM-powered applications and agentic AI workflows, including single-agent and multi-agent systems.</li><li>Build scalable RAG pipelines using embeddings, vector databases, retrieval, and prompt optimization techniques.</li><li>Develop end-to-end ML/LLM pipelines covering data ingestion, processing, model integration, inference, deployment, and monitoring.</li><li>Productionize AI solutions with observability, guardrails, security, reliability, and cost/performance optimization.</li><li>Integrate GenAI and ML solutions with enterprise applications, platforms, APIs, and business workflows.</li><li>Implement MLOps practices for model/pipeline monitoring, deployment, versioning, and operational reliability.</li><li>Collaborate with product, engineering, platform, and governance teams to deliver scalable and responsible AI solutions.</li></ul><div>Required Skills</div><div> </div><ul><li>6+ years of experience in Data Engineering, ML Engineering, Applied AI, or a related field.</li><li>Strong hands-on experience with Python and scalable data/AI systems.</li><li>Proven experience building and deploying LLM/GenAI applications in production.</li><li>Strong knowledge of RAG, embeddings, vector databases, prompt engineering, and LLM application development.</li><li>Experience with agentic AI frameworks such as LangChain, LlamaIndex, AutoGen, CrewAI, or similar.</li><li>Good understanding of ML/LLM pipelines, MLOps, monitoring, deployment, and performance optimization.</li></ul>We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status.

Collected experience requirement

4 - 7 Years