Lead Machine Learning Engineer

This job is with Morningstar, an inclusive employer and a member of my Gwork – the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly.

Title:

Lead Machine Learning Engineer

Location:

Vashi, Navi Mumbai
As a Lead Machine Learning Engineer, you will be the hands-on technical owner of ML systems that power large-scale data collection, extraction, enrichment, and understanding of unstructured content. You'll design, build, and operate end-to-end solutions-from feature generation and training to low-latency inference and observability. These solutions will measurably improve coverage, freshness, quality, and unit cost across our data pipelines. Your toolbox spans classical ML, NLP, LLMs/GenAI, Agentic AI, Retrieval-Augmented Generation (RAG) frameworks, and Model Context Protocol (MCP).

You will use these to deliver retrieval, extraction, classification, summarization, and autonomous tasking capabilities integrated cleanly into production workflows.
You'll own the architecture and implementation across AWS and GCP clouds, selecting managed services pragmatically and deploying resilient services via Docker and Kubernetes with CI/CD, autoscaling, canary/shadow releases, and tight SLIs/SLOs. You will institute MLOps best practices-experiment tracking, model and prompt registries, evaluation harnesses, data/feature drift detection, guardrails and policy enforcement, lineage and access controls-so teams can ship faster with confidence.

Day to day, you'll write production-grade Python and SQL, apply Git Hub Copilot to accelerate development responsibly, and partner with Product, Data, Platform/SRE, and Security to translate ambiguous problems into staged, observable deliveries.
You bring a curiosity to understand the domain by studying the applications, dataflow, and data schemas, and you use that context to design simpler, more accurate systems. It's a plus if you have familiarity with public and private equity data and related entity models, enabling smarter features, evaluation sets, and downstream integrations. As a lead IC, you mentor through design and code reviews, set technical direction, and improve reliability, security, and developer experience.

You will champion cost-aware, privacy-first designs; lead deep dives to resolve complex issues; and iterate quickly to achieve measurable outcomes (precision/recall, latency, error budgets, and cost per document). This role is ideal for an engineer who thrives on shipping robust ML/LLM systems at scale and influencing cross-functional teams through exceptional technical judgment and execution.
Team Overview
You will be part of a multidisciplinary team of ML engineers and data scientists responsible for building AI & ML solutions and services as part of robust data collection pipelines handling large volumes of unstructured data. Team will focus on building scalable and reliable systems to process and categorize data that is essential for downstream data collection processing.
Outline of Duties and Responsibilities
AI & ML Data Collection Leadership:  Convert business goals into a clear AI/ML roadmap for data acquisition, extraction, enrichment, and measurable outcomes.

Technical Oversight:  Architect and ship scalable ML/NLP/LLM (RAG, embeddings, reranking, Agentic AI, MCP) services with high reliability and efficiency.

Peer Leadership & Development:  Mentor engineers and data scientists through design/code reviews, setting technical standards and elevating craftsmanship.

NLP Technologies:  Build and integrate classifiers, transformers, LLMs, and evaluators that process and categorize unstructured data at scale.

Data Pipeline Engineering:  Design, operate, and optimize high-throughput collection pipelines with robust orchestration, messaging, storage, and SLAs.

Cross-functional Collaboration:

Partner with Product, Data Collection Engineering, Platform/SRE, and Security to turn ambiguous needs into phased, observable deliveries.

Innovation & Continuous Improvement:  Pilot and product ionize advances in GenAI, Agentic AI, RAG, and MCP to improve quality, speed, and cost.

System Integrity & Security:  Enforce data…