Engineer - AI/ML Operations

1 month ago

Bangalore, India Addepar Full time

Work Location - Bengaluru

The Role

Join Addepar’s innovative data and intelligence initiatives We're seeking a Software Engineer to craft and build an AI/ML Ops platform from the ground up, enabling our teams to scale AI/ML solutions efficiently

What You’ll Do

  • Build and scale a comprehensive platform, accelerating AI adoption across teams.
  • Use core Addepar systems like the Data Lakehouse to advise and strategize Ops and Data Governance infrastructure.
  • Simplify processes by promoting strategic data architecture and optimized workflows.
  • Implement data governance strategies to enhance the value of our data.

Who You Are

  • 2+ years of relevant work experience and 4+ years of overall experience that shows proficiency in platform development, particularly in enabling Machine Learning and AI outcomes.
  • Proficient in one or more cloud platforms (AWS, GCP, Azure), with hands-on experience in cloud infrastructure and handling machine learning workloads.
  • Strong expertise in CI/CD for ML pipelines—building, automating, and optimizing the pipeline lifecycle.
  • Experienced with containerization (Docker, Kubernetes) to deploy models at scale.
  • Skilled in monitoring and observability tools like FiddlerAI, Datadog, and Grafana to track model performance, data drift, and system health.
  • Knowledge of Infrastructure as Code tools (Terraform, Ansible, CloudFormation) for consistent, scalable environment setups.
  • Familiar with ML lifecycle management (Kubeflow, MLflow, TFX) to manage experiments, model versioning, and deployment.
  • A collaborative, low-ego problem-solver who takes ownership and delivers results.

Bonus points for:

  • Experience with LLM frameworks such as LangChain, Llama Index, or Semantic Kernel and LLM Observability.
  • Experience in handling large-scale datasets and high velocity data streams.
  • Proficiency with ML frameworks (TensorFlow, PyTorch).
  • Familiarity with the financial domain.
  • PySpark and Databricks experience (or similar technologies with a willingness to cross-train).

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