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 Fiddler AI, Datadog, and Grafana to track model performance, data drift, and system health.

Knowledge of Infrastructure as Code tools (Terraform, Ansible, Cloud Formation) 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 Lang Chain, Llama Index, or Semantic Kernel and LLM Observability.

Experience in handling large-scale datasets and high velocity data streams.

Proficiency with ML frameworks (Tensor Flow, Py Torch).

Familiarity with the financial domain.

Py Spark and Databricks experience (or similar technologies with a willingness to cross-train).

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