Sr. ML Engineer

Fusemachines

Completely RemoteFull TimeEngineering & Architecture
Posted Today

Job description

Responsibilities

  • Convert data science prototypes into reproducible, production-quality ML services.
  • Build and operate large-scale data and feature pipelines using Databricks, Spark, and Snowflake.
  • Own the full model lifecycle, including MLflow tracking, CI/CD, automated retraining, and drift monitoring.
  • Engineer the activation layer for governed delivery of segments and scores into DSPs, SSPs, and programmatic partners.
  • Ensure system scalability, latency, cost-efficiency, and reproducibility within an Azure environment.
  • Enforce privacy-by-design principles, including data minimization and encryption.

Requirements

  • 8–9 years of hands-on ML engineering experience shipping and operating production systems at scale.
  • Proven experience in the media, advertising, or audience activation industry.
  • Proficiency with Databricks (including MLflow and Spark), Snowflake, and Azure (ADLS, Azure ML, AKS).
  • Expert-level Python and SQL skills.
  • Strong knowledge of applied statistics, such as sampling, forecasting, or experimental design.
  • A degree in Computer Science or a related engineering field.
  • Ability to work during the second half of the day to overlap with a US-based product team.

Preferred Qualifications

  • Experience with Docker, Kubernetes, and orchestration tools like Airflow or Dagster.
  • Knowledge of Ad tech/identity concepts including DSP/SSP, DMP/CDP, and clean rooms.
  • Familiarity with AWS or GCP environments.

About the Company

Fusemachines is a leading AI strategy, talent, and education services provider on a mission to democratize AI. Founded in 2013, the company provides enterprise AI products and services to help organizations implement and scale AI across various industries, including retail, manufacturing, and government.

Skills & tools

PythonDatabricksSparkSnowflakeAzureMLflowSQL

What the team is looking for

Use this list as a quick fit check before you apply.

  1. 018–9 years ML engineering experience
  2. 02Experience shipping production systems at scale
  3. 03Media or advertising industry experience
  4. 04Proficiency in Databricks, Spark, and Snowflake
  5. 05Expert Python and SQL skills
  6. 06Strong applied statistics knowledge
  7. 07CS or engineering degree