Senior AI/ML Engineer

Overview

Senior AI/ML Engineers are senior individual contributors who design, build, and deploy production-grade AI/ML systems for both client-facing and internal products. They partner with leadership and cross-functional teams to translate business needs into scalable ML and LLM-based solutions.

Responsibilities

• AI/ML System Design & Leadership
• Lead the design and implementation of scalable ML systems, including supervised, unsupervised, and LLM-based solutions
• Translate research and prototypes into production-ready systems
• Partner with stakeholders to identify high-impact AI/ML opportunities and define optimal technical approaches
• Provide technical mentorship and contribute to team upskilling
• LLM & Production AI Systems
• Build and operate LLM pipelines, including prompt design, fine-tuning, and evaluation
• Develop RAG-based systems using embeddings, vector stores, and retrieval strategies
• Design evaluation frameworks, feedback loops, and datasets to continuously improve model performance
• Create reusable tooling to accelerate experimentation, deployment, and monitoring
• MLOps & Deployment
• Own end-to-end ML lifecycle: data pipelines, training, deployment, monitoring, and iteration
• Establish best practices for reproducibility, observability, CI/CD, and model versioning
• Partner with platform/DevOps teams to ensure reliability and scalability
• Promote responsible AI practices, including governance, fairness, and transparency
• Cross-Functional Collaboration
• Lead cross-functional initiatives across data engineering, analytics, and AI/ML
• Translate complex ML concepts into clear recommendations for technical and non-technical audiences
• Collaborate with clients and internal teams to plan and deliver AI/ML solutions
• Contribute documentation, frameworks, and shared best practices
• Project Execution
• Scope and lead complex AI/ML initiatives aligned to business outcomes
• Align stakeholders and drive execution across teams
• Establish clear success metrics and ensure delivery of high-impact solutions

Skills & Qualifications

• 5–7 years of experience in ML engineering, AI engineering, or related fields, with production deployment experience
• Strong programming skills in Python and SQL; experience with PyTorch and HuggingFace
• Experience building LLM applications, including RAG, embeddings, and vector search
• Experience with cloud platforms (AWS or Azure; e.g., SageMaker, Bedrock, Azure ML)
• Strong understanding of ML fundamentals: data design, training, evaluation, and experimentation
• Familiarity with LLM alignment techniques (e.g., SFT, DPO, RL)
• Experience with MLOps practices: CI/CD, monitoring, retraining, and experiment tracking
• Proficiency working with complex, multi-source datasets and defining evaluation strategies
• Strong software engineering fundamentals (testing, modularity, code review)
• Experience mentoring engineers and influencing technical direction
• Strong communication skills with both technical and non-technical stakeholders

Tech Stack

• Languages: Python, SQL
• Frameworks: PyTorch, HuggingFace
• Platforms: AWS, Azure, Snowflake, Databricks

Physical Requirements

Frequent sitting at a desk performing work on a computer

Compensation Range

$175,000 - 190,000 annually

Core Company Values

• Take the Long View - Ensure the company is built to last
• Be Courageous - Make the right decisions even when they aren't the easiest decisions
• Be Genuine - Bring honesty and authenticity to all that you do
• Work with Focus + Passion - Display purpose and pride in your work and never stop learning

Equal Opportunity Employer

We are firmly committed to diversity, equity, and inclusion in our hiring efforts. We recognize that we need team members from all backgrounds and experiences to successfully shape a positive employee experience as well as deliver our product and service solutions. To that end, we actively seek candidates who can bring diverse experiences and backgrounds to our team.

Application Information

Please note that compensation packages are finalized after the interview process is concluded. We use a competency-based approach to base pay, which means it is based on the competencies and skills demonstrated for this role.

To apply for this job, please visit our careers page and submit your application.