Raft is hiring a
Senior AI/ML Engineer

Summary

The job is for a Senior AI/ML Engineer at Raft, a U.S.-based small business focusing on Distributed Data Systems, Platforms at Scale, and Complex Application Development. The role involves developing Machine Learning models and requires 5 years of experience, proficiency in Python, and knowledge of various ML subfields. The position is remote with potential travel.

Requirements

• 5 years of relevant hands-on experience
• Strong practical experience in Software Engineering
• Practical experience designing, training, and deploying Machine Learning models (PyTorch preferred)
• Experience with Kubernetes and Docker
• Pragmatic knowledge of various ML subfields, especially NLP, CV, and Time Series
• A passion for innovation, an interest in exploring and leveraging new data modalities, and working across interdisciplinary teams
• Experience building and maintaining machine learning pipelines
• Experience in using data processing frameworks (Apache Spark preferred)
• Practical programming and scripting skills (Python preferred)
• Fast learner, analytical thinker, creative, hands-on, strong communication skills
• Able to work both independently and as part of a team
• Excellent problem-solving skills and attention to detail
• Proven experience with modern software development and engineering practices including scrum/agile, Git, and DevOps
• Obtain Security+ within the first 90 days of employment with Raft

Responsibilities

Develop Machine Learning models that are integral to a larger pipeline delivering value to end customers

Preferred Qualifications

• Publications or GitHub repos showcasing your skills
• Experience with TypeScript
• Prior work with LLM’s and Agentic Workflows

Benefits

• Highly competitive salary
• Fully covered healthcare, dental, and vision coverage
• 401(k) and company match
• Take as you need PTO + 11 paid holidays
• Education & training benefits
• Annual budget for your tech/gadgets needs
• Monthly box of yummy snacks to eat while doing meaningful work
• Remote, hybrid, and flexible work options
• Team off-site in fun places!
• Generous Referral Bonuses