Senior ML Engineer - AI Pipelines & MLOps Lead

100 Salesforce, Inc.; San Francisco (CA); On-site; USD 173,000 - 260,000; Full time

Benefits offered by this job

Time off programs

Medical insurance

Dental insurance

Vision care

Mental health support

Paid parental leave

Life and disability insurance

401(k)

Employee stock purchasing program

Job summary

Salesforce, the Customer Company, seeks a hands-on Lead Machine Learning Engineer to define and execute the technical ML strategy within the Trust Intelligence Platform. You will own multiple ML pipelines, emphasize MLOps, CI/CD, and model monitoring, and mentor engineers while collaborating with cross‑functional teams.

The role focuses on productionizing Generative AI solutions, cost-efficient model optimization, and implementing infrastructure‑as‑code across security and compliance domains.

Qualifications

• Masters or PhD in a quantitative field.
• 6+ years end-to-end lifecycle of multi-model ML systems.
• Deep understanding of containerization (Docker) and workflow orchestration (Kubernetes, Apache Airflow).
• Mastery of Python and ML frameworks (TensorFlow, PyTorch).
• Experience implementing MLOps, CI/CD pipelines, testing and model monitoring.
• Foundation in feature engineering and feature stores.
• Experience deploying generative AI solutions.
• Proficiency with infrastructure-as-code, monitoring tools, and big data tech (Spark, Snowflake).
• Experience with ML governance and data security compliance.
• Track record delivering measurable business outcomes across teams.

Responsibilities

• Define and drive the technical ML strategy with robust model architectures and MLOps practices.
• Lead end-to-end development of ML pipelines, including automated retraining and cost/performance optimization.
• Own a portfolio of ML pipelines within security and compliance domains.
• Implement infrastructure-as-code, CI/CD, and MLOps automation with monitoring and drift detection.
• Collaborate with Data Science, Data Engineering, Research and Product Management to deliver scalable ML solutions; mentor juniors.

Skills

Docker

Kubernetes

Apache Airflow

Python

TensorFlow

PyTorch

MLOps

CI/CD

Monitoring

Feature stores

Spark

Snowflake

Generative AI

Security/Compliance

Education

Masters or PhD in a quantitative field

Tools

Docker

Kubernetes

Apache Airflow

Spark

Snowflake

TensorFlow

PyTorch

Job description

Salesforce, the Customer Company, seeks a hands-on Lead Machine Learning Engineer to define and execute the technical ML strategy within the Trust Intelligence Platform. You will own multiple ML pipelines, emphasize MLOps, CI/CD, and model monitoring, and mentor engineers while collaborating with cross‑functional teams.

The role focuses on productionizing Generative AI solutions, cost-efficient model optimization, and implementing infrastructure‑as‑code across security and compliance domains.