Title: Senior Machine Learning Engineer 

Department: Data Intelligence

Reports To: Senior Manager, Data Intelligence

FLSA Status: Exempt 

Location: US Remote

Job Summary

We are looking for a Senior Machine Learning Engineer to join our team and play a critical role in bridging data science and software engineering. In this role, you will partner with data scientists to take models from prototype to production, and with software engineers to build APIs and services that are performant, reliable, and scalable. You’ll be responsible for ensuring that machine learning systems are production-ready, monitored, and continuously improved.

This position is ideal for someone who thrives at the intersection of machine learning, software engineering, and MLOps.

Key Responsibilities

• Model Deployment & Integration
• Collaborate with data scientists to transform research models into production-ready services.
• Design, build, and maintain APIs and microservices to serve ML models at scale.
• Ensure smooth integration of ML solutions into core products and platforms.
  
  
• Performance & Reliability
• Optimize inference performance, latency, and scalability.
• Build monitoring, logging, and alerting systems to track model performance and data drift.
• Implement retraining pipelines and automated workflows for continuous improvement.
  
  
• Engineering & MLOps
• Develop CI/CD pipelines for machine learning workflows.
• Use modern DevOps/MLOps practices to ensure reproducibility and reliability.
• Partner with software engineers to design robust data and compute infrastructure.
  
  
• Collaboration & Leadership
• Work closely with cross-functional teams to align model capabilities with business needs.
• Mentor junior engineers and contribute to best practices in ML engineering.
• Advocate for scalable, sustainable ML deployment strategies across the organization.

Qualifications

• Education & Experience
• 5-7+ years of professional experience in ML engineering, software engineering, or related roles.
• Bachelor’s Master’s in Computer Science, Engineering, or related field (required).
• Master’s in Computer Science, Engineering, or related field, or equivalent experience (preferred).

• Technical Skills
• Strong programming skills in Python (and experience with libraries such as scikit-learn, TensorFlow, or PyTorch), Java, and/or Go.
• Hands-on experience building APIs and services (e.g., FastAPI, Flask, gRPC).
• Expertise with containerization & orchestration (Docker, Kubernetes).
• Familiarity with CI/CD pipelines and modern MLOps tools (MLflow, Airflow, Kubeflow, SageMaker, or similar).
• Strong understanding of cloud platforms (AWS).
• Solid background in data pipelines, distributed systems, and performance optimization.
  
  
• Soft Skills
• Strong collaboration skills with both data scientists and software engineers.
• Ability to balance technical rigor with pragmatic delivery.
• Excellent communication and problem-solving abilities.

What We Offer

• Competitive compensation and benefits.
• Opportunities to shape end-to-end ML systems in production.
• A collaborative, high-impact environment where ML solutions directly drive business outcomes.

This position description should not be considered the final description of the position. The position description is not intended to be an all-inclusive list of duties and standards of the positions. It should be assumed that we would, to some extent, structure responsibilities in accordance with the successful candidate’s capabilities and changing business conditions. Incumbents will follow any other instructions, and perform any other related duties, as assigned by their supervisor.

The anticipated salary range for this role is $180,000 - $190,000 plus variable commission / company bonus. Offered salary will be determined by the applicant’s education, experience, knowledge, skills, geo-location and abilities, as well as internal equity and alignment with market data.