Senior ML Engineer (ML/AI)

Design, train, fine-tune, and evaluate deep learning, classical ML, and foundational GenAI models (LLMs, diffusion models) to drive core product features.

Build, scale, and maintain robust ML pipelines for continuous training, evaluation, and real-time/batch inference using modern MLOps frameworks.

Collaborate with backend and frontend teams to integrate AI models into microservices, ensuring low latency, high availability, and optimal resource utilization.

Architect scalable data pipelines for preprocessing, vectorizing, and ingestion of massive structured and unstructured datasets.

Implement rigorous evaluation frameworks for model alignment, bias mitigation, guardrailing, and cost/latency optimization (e.g., quantization, distillation).

Provide technical leadership, conduct thorough code reviews, and mentor junior/mid-level engineers on best practices in software craftsmanship and ML engineering.

6+ years of experience deploying ML/AI solutions in production environments

Ability to write high-quality code in Python

Experience building RAG (retrieval-augmented generation) based solutions

Experience setting up and maintaining vector databases

A strong desire to work on ML/AI based products

A desire to learn new technologies quickly

A thoughtful approach to balancing quality and deadlines in fast-paced settings

Excellent communication skills with a talent for building consensus and alignment

Strong organizational skills and the ability to distill complex problems into clear priorities that move the team and business forward

Experience defining and using Protobuf messages

Experience working with Docker and deploying applications to Kubernetes

Experience with relational and low-latency databases

Experience working with Celery

Experience building RAG (retrieval-augmented generation) based solutions

Experience setting up and maintaining vector databases

Experience writing production code in Java/Kotlin

Experience building solutions on cloud infrastructure, particularly AWS

Experience working with highly sensitive data in a healthcare environment