Machine Learning Research Engineer, Generative AI

Performant model code, high quality data, and robust evaluation methods form the foundation of an AI system. Scale’s leading end-to-end solutions for the ML lifecycle based on real-world data will continue to set the bar for the data-centric AI movement. Scale’s Generative AI team focuses on building models to accelerate AI adoption for some of the largest companies in the world. 

 Your focus will be on developing Models as a Service using a variety of Machine Learning techniques. You will be involved end-to-end from coordinating with operations to create high quality datasets to productionizing models for our customers. If you are excited about shaping the future of the data-centric AI movement, we would love to hear from you!

You will: 

• Apply state of the art models, developed both internally and from the community, in production to solve problems for our customers and data labelers. 
• Work with product and research teams to identify opportunities for ongoing and upcoming services.
• Explore approaches that integrate human feedback and assisted evaluation into existing product lines. 
• Work closely with customers - some of the most sophisticated ML organizations in the world - to quickly prototype and build new deep learning models targeted at multi-modal content understanding problems.

Ideally you’d have:

• At least 3 to 5 years of model training, deployment and maintenance experience in a production environment
• Strong skills in NLP, LLM and deep learning 
• Solid background in algorithms, data structures, and object-oriented programming
• Experience working with cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment

Nice to haves:

• Experience in dealing with large scale AI problems, ideally in the generative-AI field
• Demonstrated expertise in large vision-language models for diverse real-world applications, e.g. classification, detection, question-answering, etc. 
• Published research in areas of machine learning at major conferences (NeurIPS, ICML, EMNLP, CVPR, etc.) and/or journals
• Strong high-level programming skills (e.g., Python), frameworks and tools such as DeepSpeed, Pytorch lightning, kuberflow, TensorFlow, etc. 
• Strong written and verbal communication skills to operate in a cross functional team environment

The base salary range for this full-time position in our hub locations of San Francisco, New York, or Seattle, is $176,000 - $240,960. Compensation packages at Scale include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Scale employees are also granted Stock Options that are awarded upon board of director approval. You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.