LMTS Machine Learning Engineer Job at Salesforce in new york

Job Category: Software Engineering

About Salesforce

Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn't a buzzword - it's a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all.

About the Role

We are seeking a highly skilled Machine Learning Engineer to design, build, and productionalize models that drive customer growth, engagement and retention. This role will focus specifically on attrition prediction and mitigation – identifying customers at risk of churn and surfacing proactive interventions that improve customer satisfaction and lifetime value.

What You’ll Do

• Design predictive models for user and customer attrition using supervised, unsupervised, deep learning, and generative techniques.
• Design scalable data pipelines for feature generation from both structured and unstructured sources of product adoption, sales activity, and customer engagement data (e.g. product telemetry, usage logs, CRM, sales activity).
• Build and maintain production‑grade ML services, integrating models into APIs or decision systems that support real‑time and batch use cases.
• Continuously monitor and improve model performance through drift detection, retraining automation, and impact measurement.
• Collaborate with product and engineering teams to integrate models into production systems and agentic experiences, ensuring scalability, robustness, and efficiency.
• Mentor junior engineers and data scientists and provide technical leadership in model architecture, experimentation, and deployment best practices.

What We’re Looking For

• Demonstrated ability to take models from research to production.
• Strong software engineering proficiency in Python and data manipulation skills like SQL.
• Experience using third‑party and in‑house machine learning tools and infrastructure to develop reusable, high‑performing ML systems, enable fast model development, low‑latency serving and ease of model quality upkeep.
• Exposure to architectural patterns of a large, high‑scale software application (e.g. well‑designed APIs, high‑volume data pipelines, efficient algorithms).
• Familiarity with ML libraries such as scikit‑learn, XGBoost, PyTorch, or TensorFlow.
• Experience with feature engineering on big data (Spark, Trino, Snowflake).
• Experience with ML lifecycle management tools (MLflow, Airflow, Kubeflow or equivalents).
• Experience with containerization technologies (Docker) and orchestration (Kubernetes).
• Strong grasp of model evaluation, drift monitoring, and explainability best practices.
• Experience with Agile development methodology, Test‑Driven Development, incremental delivery, and CI/CD.
• Experience owning and operating services throughout the software development lifecycle including design, development, release and maintenance.
• Experience communicating technical vision, mentoring junior engineers and managing projects.
• Experience developing and evaluating AI Agents that integrate with traditional ML models (e.g. combining predictive scoring systems with generative or agentic workflows to automate customer engagement flows and recommendations).

Preferred Qualifications (Bonus Points)

• Familiarity with retention modeling or next‑best‑action recommendation systems.
• Experience developing or contributing to shared ML frameworks or internal ML Ops platforms.
• Experience with Feature Stores like Feast.

Accommodations

If you need a reasonable accommodation during the application or the recruiting process, please submit a request via the Accommodations Request Form.

Posting Statement

Salesforce is an equal‑opportunity employer and maintains a policy of non‑discrimination with all employees and applicants for employment. We believe in equality for all and work toward an inclusive workplace that is free from discrimination. Applicants will be assessed on the basis of merit, competency and qualifications without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint or other classifications protected by law.

Benefits and Compensation

In the United States, compensation offered will be determined by factors such as location, job level, job‑related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. Salesforce offers a variety of benefits to help you live well including: time‑off programs, medical, dental, vision, mental health support, paid parental leave, life and disability insurance, 401(k), and an employee stock‑purchasing program. The typical base salary range for this position is $172,500 – $260,100 annually; in select cities within the San Francisco and New York City metropolitan area, the range is $207,800 – $285,800 annually. The range represents base salary only, and does not include company bonus, incentive for sales roles, equity or benefits, as applicable.

#J-18808-Ljbffr