Senior Engineer - ML / AI ops
Job details
Who We Are Addepar is a global technology and data company that helps investment professionals provide the most informed, precise guidance for their clients. Hundreds of thousands of users have trusted Addepar to empower smarter investment decisions and better advice over the last decade. With client presence in more than 40 countries, Addepar’s platform aggregates portfolio, market and client data for over $5 trillion in assets. Addepar’s open platform integrates with more than 100 software, data, and services partners to deliver a complete solution for a wide range of firms and use cases. Addepar embraces a global flexible workforce model with offices in Silicon Valley, New York City, Salt Lake City, Chicago, London, Dublin, Edinburgh, Scotland and Pune, India.
- Marketplace and brokerage services are provided by Acervus Securities, Inc., an SEC-registered broker‑dealer and member of FINRA / SIPC.
- Build and scale a comprehensive platform, accelerating AI adoption across teams.
- Collaborate with product managers and engineers to define requirements, and architect solutions for sophisticated data and workflow challenges.
- 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.
- 6+ years of relevant work experience and 8+ 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.
- Experienced in securing ML systems and ensuring compliance with regulations (e.g., GDPR).
- A collaborative, low-ego problem-solver who takes ownership and delivers results.
- Experience with Data Governance initiatives
- 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).
- Act Like an Owner - Think and operate with intention, purpose and care. Own outcomes.
- Build Together - Collaborate to unlock the best solutions. Deliver lasting value.
- Champion Our Clients - Exceed client expectations. Our clients’ success is our success.
- Drive Innovation - Be bold and unconstrained in problem solving. Transform the industry.
- Embrace Learning - Engage our community to broaden our perspective. Bring a growth mindset.
Apply safely
To stay safe in your job search, information on common scams and to get free expert advice, we recommend that you visit SAFERjobs, a non-profit, joint industry and law enforcement organization working to combat job scams.