We are looking for a Lead ML Engineer to take full ownership of the customer next-generation search platform. You will bridge advanced information retrieval (IR) modeling with high-throughput production systems — building, tuning, and scaling hybrid search pipelines while owning the evaluation harness, performance benchmarks, and master data integrations that guarantee extreme precision and sub-second latency at scale.
This is a high-impact, end-to-end engineering role. You will shape the architecture of a system that directly affects the experience of millions of customers, while mentoring talented engineers and partnering closely with product and data stakeholders.
WHAT YOU'LL DO
Design, build, and tune a hybrid search engine combining Vector Search (semantic) and Lexical Search (BM25/keyword) to deliver best-in-class relevance.
Implement advanced ranking and blending strategies including BGE rerankers and Reciprocal Rank Fusion (RRF).
Own end-to-end search accuracy and relevance metrics (NDCG, MRR, Recall) and drive measurable, data-backed improvements over time.
Build and maintain an automated accuracy evaluation harness for continuous, regression-proof pipeline testing.
Establish quality benchmarks and champion a metrics-first engineering culture across the team.
Conduct systematic load testing (Locust, k6) and stress-test retrieval pipelines to surface and eliminate bottlenecks.
Architect and optimize systems to guarantee a strict SLA of P95 latency < 500ms under peak production load.
Partner with DevOps/MLOps to design scalable, resilient deployment patterns for search and ranking models.
Manage ingestion pipelines for Master Data Management (MDM) feed integration, ensuring clean and timely data synchronisation.
Govern schema and operational configurations within the Firestore spec_registry.
Collaborate with data governance teams to uphold data quality standards across all search indexes.
Mentor junior and mid-level engineers through code reviews, pairing, and technical guidance.
Lead cross-functional AI/ML project teams, translating business requirements into clear technical roadmaps.
Communicate complex architectural decisions clearly to both technical peers and non-technical stakeholders.
Search Core & Information Retrieval
Evaluation & Quality Assurance
Performance, Scalability & Infrastructure
Data Engineering & Governance
Leadership & Collaboration
WHAT WE'RE LOOKING FOR
Deep hands-on experience with vector databases (Pinecone, Milvus, Qdrant) and search engines (Elasticsearch, OpenSearch)Proven experience implementing reranking models (BGE, Cohere) and fusion techniques (RRF) in production. Expertise in load testing with Locust or k6 and diagnosing distributed system bottlenecks. Experience integrating enterprise MDM feeds and managing NoSQL stores, specifically Google Cloud Firestore.
Strong background applying ML techniques to search relevance, ranking, and personalisation. Hands-on experience with LLMs or GenAI for search retrieval and knowledge synthesis.
Solid grounding in statistical evaluation for search quality and system reliability.
10+ years of professional experience in Machine Learning and AI engineering.
Google Cloud Professional Machine Learning Engineer or TensorFlow Developer Certification.
Hands-on experience with MLOps, CI/CD pipelines, and orchestration tools (Kubeflow, Airflow, Dagster).
Familiarity with model serving and monitoring frameworks ( Vertex AI, Azure ML etc)
Demonstrated track record of mentoring engineers and leading cross-functional AI/ML projects.
Experience in Computer Vision or Recommender Systems.
Familiarity with knowledge graph construction or entity resolution pipelines.
Prior exposure to e-commerce or supply chain search use cases.
Core Technical Skills
Must-Have Qualifications
Nice to Have
EDUCATION
Minimum: B.Tech. / B.E. in Computer Science, Information Technology, or a related field.
Preferred: Master’s degree (M.S. / M.Tech.) in Machine Learning, Data Science, or Artificial Intelligence.
Skills Required
- At least 5 years designing and building ML/AI applications and deploying them to production
- At least 8 years software engineering experience building secure, scalable, performant applications
- At least 2 years leading and mentoring ML/data science teams (4+ members)
- Experience with document extraction using AI, Conversational AI, Vision AI, NLP or Generative AI
- Design, develop, and operationalize ML models by fine-tuning and personalization
- Evaluate machine learning models and perform necessary tuning
- Develop prompts and perform prompt engineering for LLMs
- Collaborate on dataset analysis and preprocessing (cleaning, transformation, augmentation)
- Analyze LLM responses and iteratively improve prompts and performance
- Lead end-to-end design and architecture of scalable Generative AI solutions, including RAG pipelines and agentic workflows
- Hands-on customer experience with RAG solutions or fine-tuning LLM models
- Build and deploy scalable ML pipelines on GCP or equivalent cloud platforms (data warehouses, ML platforms, dashboards, CRM integrations)
- End-to-end ML workflow experience: data cleaning, EDA, outlier handling, imbalance handling, feature engineering, model selection, training, deployment
- Write clean, high-quality, scalable code for prompt engineering, vector search, data processing, model evaluation, and inference serving
- Proven experience building and deploying ML models in production
- Good understanding of NLP, computer vision, or other deep learning techniques
- Expertise in Python, NumPy, Pandas and ML libraries (XGBoost, TensorFlow, PyTorch, scikit-learn, LangChain)
- Familiarity with Google Cloud or other cloud platforms
- Google Cloud Professional ML or TensorFlow Developer certification (Good to have)
- Experience with GCP, AWS or Azure (preferred)
- Experience with AutoML and vision techniques (preferred)
- Master's degree in statistics, machine learning, or related field (preferred)
What We Do
Egen is a data engineering and cloud modernization firm partnering with leading Chicagoland companies to launch, scale, and modernize industry-changing technologies. We are catalysts for change who create digital breakthroughs at warp speed. Our team of cloud and data engineering experts are trusted by top clients in pursuit of the extraordinary. Our mission is to be an enabler of amazing possibilities for companies looking to use the power of cloud and data. We want to stand shoulder to shoulder with clients, as true technology partners, and make sure they succeed at what they have set out to do. We want to be disruptors, game-changers, and innovators who have played an important part in moving the world forward.
