Machine Learning Engineering Manager, Enterprise

1 Month ago • All levels • Research Development • $212,000 PA - $254,400 PA

Job Summary

Job Description

Scale is seeking an AI data foundry to accelerate the development of AI applications. The ML team interfaces directly with clients to build cutting-edge products using proprietary research and resources. As an ML Engineering Manager, you will manage a team of Applied AI Engineers and ML Engineers who train ML models to meet client business needs. Your team's work will involve training next-generation AI cybersecurity firewall LLMs and foundation agentic action models. You will guide your team in using data-driven experiments to provide insights into model strengths and inefficiencies to improve products.
Must have:
  • 3+ years model training, deployment, and maintenance experience in production
  • 1-2 years management or tech leadership experience
  • Strong skills in NLP, LLMs, and deep learning
  • Solid background in algorithms, data structures, and OOP
  • Experience with cloud technology stack (AWS/GCP)
  • Experience building products with LLMs
  • PhD or Master's in Computer Science or related field
Good to have:
  • Experience with large-scale AI problems, especially generative AI
  • Expertise in large vision-language models
  • Published research in machine learning conferences/journals
  • Strong programming skills (Python) and tools (DeepSpeed, Pytorch lightning, kubeflow, TensorFlow)
  • Strong written and verbal communication skills
Perks:
  • Comprehensive health, dental and vision coverage
  • Retirement benefits
  • Learning and development stipend
  • Generous Paid Time Off (PTO)
  • Commuter stipend

Job Details

AI is becoming vitally important in every function of our society. At Scale, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re accelerating the usage of frontier data and models by building complex agents for enterprises around the world through our Scale Generative AI Platform (SGP).

The SGP ML team works on the front lines of this AI revolution. We interface directly with clients to build cutting edge products using the arsenal of proprietary research and resources developed at Scale. As an ML Engineering Manager, you’ll manage a team of high-calibre Applied AI Engineers + MLEs who work with clients to train ML models to satisfy their business needs. Your team’s work will range from training next-generation AI cybersecurity firewall LLMs to training foundation agentic action models making predictions about business-saving outcomes. You will guide your  team towards using data-driven experiments to provide key insights around model strengths and inefficiencies in an effort to improve products. If you are excited about shaping the future of the modern AI movement, we would love to hear from you!

You will:

  • Train state of the art models, developed both internally and from the community, in production to solve problems for our enterprise customers. 
  • Manage a team of 5+ Applied AI Engineers / ML Engineers
  • 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. 
  • Create state of the art techniques to integrate tool-calling into production-serving LLMs.
  • 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 years of model training, deployment and maintenance experience in a production environment
  • At least 1-2 years of management or tech leadership experience
  • Strong skills in NLP, LLMs and deep learning 
  • Solid background in algorithms, data structures, and object-oriented programming
  • Experience working with a cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment
  • Experience building products with LLMs including knowing the ins and outs of evaluation, experimentation, and designing solutions to get the most of the models
  • PhD or Masters in Computer Science or a related field

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, kubeflow, TensorFlow, etc. 
  • Strong written and verbal communication skills to operate in a cross functional team environment

Compensation packages at Scale for eligible roles 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. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. 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.

Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:

$212,000 - $254,400 USD

PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.

About Us:

At Scale, we believe that the transition from traditional software to AI is one of the most important shifts of our time. Our mission is to make that happen faster across every industry, and our team is transforming how organizations build and deploy AI.  Our products power the world's most advanced LLMs, generative models, and computer vision models. We are trusted by generative AI companies such as OpenAI, Meta, and Microsoft, government agencies like the U.S. Army and U.S. Air Force, and enterprises including GM and Accenture. We are expanding our team to accelerate the development of AI applications.

We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. 

We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information.

We comply with the United States Department of Labor's Pay Transparency provision

PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

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