Sr. ML Engineer

Fusemachines; India; Remote; INR 4,000,000 - 9,000,000; Full time

Job summary

Fusemachines is seeking a senior ML engineer to transform data science prototypes into scalable, production-grade ML services. You will own end-to-end pipelines, model lifecycle, and activation layers across DSPs, DMPs, and clean rooms while mentoring peers and setting engineering standards.

Responsibilities include building large-scale data pipelines on Databricks/Spark, managing CI/CD, automated retraining, and ensuring privacy-by-design across Azure-based platforms.

Qualifications

• 8–9 years hands-on ML engineering, shipping and operating production systems at scale.
• Prior experience in media / advertising / audience activation.
• Expert Python and ML ecosystem; strong SQL at scale.

Responsibilities

• Convert data science prototypes into production-quality ML services.
• Build and operate large-scale data/feature pipelines on Databricks + Spark.
• Own the full model lifecycle: MLflow tracking/registry, CI/CD, retraining, drift monitoring.
• Engineer the activation layer, delivery of segments into DSPs/SSPs, DMP/CDP, clean rooms, and CTV/social/programmatic partners.
• Ensure scalability, latency, cost-efficiency, and reproducibility across Azure services.
• Enforce privacy-by-design: data minimization, access controls, encryption, clean-room patterns.

Skills

ML engineering

Databricks

Snowflake

Azure

Python

SQL

Statistics

Education

CS/Engineering degree

Tools

Databricks

Snowflake

Azure

Docker/Kubernetes

Job description

About Fusemachines Fusemachines is a leading AI strategy, talent, and education services provider. Founded by Sameer Maskey Ph.D., Adjunct Associate Professor at Columbia University, Fusemachines has a core mission of democratizing AI. With a presence in 4 countries (Nebal?). Founded in 2013, Fusemachines is a global provider of enterprise AI products and services, on a mission to democratize AI. Leveraging proprietary AI Studio and AI Engines, the company helps drive the clients’ AI Enterprise Transformation, regardless of where they are in their Digital AI journeys. With offices in North America, Asia, and Latin America, Fusemachines provides a suite of enterprise AI offerings and specialty services that allow organizations of any size to implement and scale AI. Fusemachines serves companies in industries such as retail, manufacturing, and government. Fusemachines continues to actively pursue the mission of democratizing AI for the masses by providing high-quality AI education in underserved communities and helping organizations achieve their full potential with AI.

Type: Remote, Full-time

About the role

Turn audience science into scalable production systems that help advertisers decide whom to reach. Working with terabyte-scale data, you'll build, score, refresh, and deliver audience segments to activation endpoints across DSPs, clean rooms, CTV, social, and programmatic partners. You bridge data science and platform engineering—converting prototypes into production-grade services and owning the pipelines, MLOps, and integrations behind them. As a senior team member, you'll set engineering standards, lead end-to-end system design, and mentor other engineers. Stack: Databricks, Spark, Snowflake, and Azure.

Responsibilities

• Convert data science prototypes (propensity, lookalike, segmentation, fusion) into reproducible, production-quality ML services.
• Build and operate large-scale data/feature pipelines on Databricks + Spark, reading from and writing to Snowflake, producing versioned audience segments on schedule.
• Own the full model lifecycle: MLflow tracking/registry, CI/CD (Azure DevOps or GitHub Actions), automated retraining, drift monitoring, and rollback.
• Engineer the activation layer, governed delivery of segments and scores into DSPs/SSPs, DMP/CDP, clean rooms, and CTV/social/programmatic partners, including identity resolution and onboarding.
• Ensure scalability, latency, cost-efficiency, and reproducibility across Azure (ADLS, Azure ML, AKS); support batch and near-real-time scoring.
• Enforce privacy-by-design: data minimization, access controls, encryption, and clean-room-compatible patterns.

Essential qualifications

• 8–9 years hands-on ML engineering, shipping and operating production systems at scale.
• Prior experience in media / advertising / audience activation.
• Databricks (incl. MLflow and Spark), Snowflake, and production Azure (ADLS, Azure ML, Azure DevOps, AKS).
• Expert Python and ML ecosystem; strong SQL at scale.
• Strong applied statistics (sampling/weighting, forecasting, causal inference, or experimental design).
• CS/engineering degree with strong quantitative foundations.

Desirable

• Agile practices, Docker/Kubernetes, advanced Databricks/Snowflake (Structured Streaming, tuning, Model Serving/Feature Store), orchestration (Databricks Workflows, Airflow, Dagster).
• Ad tech/identity experience: DSP/SSP, DMP/CDP, clean rooms (LiveRamp, Snowflake), identity graphs, onboarding, delivery APIs.
• AWS/GCP a plus.

About you

Pragmatic and deeply hands-on about production trade-offs; a clear communicator with non-expert stakeholders; a proactive team player who mentors others. Comfortable working the second half of the day to overlap with a US-based product team. Fluent in an English-language business environment.

Fusemachines is an Equal Opportunities Employer, committed to diversity and inclusion. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or any other characteristic protected by applicable federal, state, or local laws.

Originally posted on Himalayas