Machine Learning Engineer

Machine Learning Engineer

Key Responsibilities

• Design, build, and optimize

  feature engineering pipelines

  and

  feature stores

  .
• Implement

  RAG pipelines

  , LLM-based solutions, and GPU-accelerated workflows.
• Develop scalable

  model serving

  architectures with high availability and low latency.
• Manage

  ML incidents

  , monitor system performance, and ensure reliable deployments.
• Build and maintain

  microservices

  for ML components using Java/Spring Boot or FastAPI.
• Develop robust

  REST APIs

  for model inference and ML-driven services.
• Conduct

  A/B testing

  , monitor model drift, and improve model performance.
• Work with

  distributed systems

  (Spark, Spark Streaming, HDFS) for large-scale data processing.
• Implement data streaming pipelines using

  Kafka

  and caching layers using

  Redis

  .
• Collaborate with data scientists, backend engineers, and DevOps teams to deliver high-quality ML solutions.
  

Required Skills & Qualifications

• 4-7 years of experience in Machine Learning Engineering or related fields.
• Strong experience with

  RAG

  ,

  LLMs

  , model deployment, and GPU-based model pipelines.
• Expertise in

  feature engineering

  ,

  feature pipelines

  , and ML observability.
• Strong backend development experience with

  Java

  ,

  Spring Boot

  ,

  FastAPI

  , and

  REST APIs

  .
• Hands-on experience with

  Kafka

  ,

  Redis

  ,

  NoSQL databases

  , and

  feature stores

  .
• Experience with distributed computing frameworks:

  Spark

  ,

  Spark Streaming

  ,

  HDFS

  .
• Proficiency in

  A/B testing

  , model monitoring, and large-scale ML evaluation.
• Strong understanding of

  microservices

  ,

  distributed systems

  , and scalable architecture.

Preferred Skills (Good to Have)

• Experience deploying LLM applications in production.
• Knowledge of Kubernetes, Docker, and MLOps platforms.
• Familiarity with experiment tracking tools (MLflow, Weights & Biases, etc.).
• Exposure to cloud platforms (AWS, GCP, Azure).
  

What We Offer

• Competitive compensation up to

  75 LPA

  .
• Opportunity to work on cutting-edge

  LLM and ML infrastructure

  .
• Work with a high-performing engineering team solving large-scale problems.
• Fast-paced, innovation-driven environment.