Applied Machine Learning Engineer, Snorkel AI
$140-200k
+ Stock Options
Data-centric enterprise AI platform for
Open for applications
Data-centric enterprise AI platform for
101-200 employees
Open for applications
$140-200k
+ Stock Options
101-200 employees
Company mission
To empower everyone to solve their most impactful problems through data-centric AI.
Role
Who you are
- 5+ years of professional experience with machine learning, or 2+ years of professional experience with machine learning with an advanced degree in a relevant field
- 1+ year of professional experience working directly with external customers to scope out build machine learning models, tools, or services
- Expertise in modern machine learning frameworks and technologies (e.g. PyTorch, Transformers, Scikit-learn, NumPy, Pandas), and an obsession with thorough ML evaluation
- Experience building and maintaining large scale, production data pipelines for machine learning applications
- Ability to work in a fast-paced environment and strong technical communication skills
What the job involves
- As an Applied Machine Learning Engineer, you’ll research and utilize established and state-of-the-art machine learning (ML) techniques to successfully deliver solutions to our customers
- You'll engage new ML use cases through hands-on customer problems and help generalize learnings into the core Snorkel Flow platform
- Assist customers with the delivery of a Machine Learning project from beginning to end, including business case definition and scoping, data aggregation and exploration, algorithm selection, and model deployment to deliver business impact to the organization
- Present findings and recommendations to customer stakeholders, assist with program ideation and technical program management, and brief materials
- Design, develop, and deploy enterprise AI/ML solutions across various industries like finance, healthcare, insurance, retail and more
- Serve as the voice of our customers for new ML paradigms, data science workflows, and share customer feedback to product teams
Our take
Demand for AI is increasing in almost every industry, but the machine learning that fuels it is tedious to set up. In order to train machine learning algorithms, training data must be labelled manually, and this contributes to expenses in time, money and resources when integrating AI within a business.
Snorkel AI develops programmatic approaches to data labelling in order to automate the setup process of machine learning and decrease the required timeframe for a business to begin providing AI services. In addition to these automated data categorization services, the company also integrates data training, management, and analysis into a unified AI-deployment platform.
The complex computer science behind AI setup has resulted in many businesses without computer science backgrounds being left behind, and Snorkel AI has set this as their target audience. As of 2023, this customer base has tripled in size since Snorkel AI's founding and in 2024, enjoyed a new round of funding. With these promising developments, the company continues to innovate the sector.
Kirsty
Company Specialist
Insights
Some candidates hear
back within 2 weeks
-13% employee growth in 12 months
Company
Funding (last 2 of 3 rounds)
Aug 2021
$85m
SERIES C
Apr 2021
$35m
SERIES B
Total funding: $135m
Company benefits
- Home office allowance
- Yearly wellness stipend
- Healthy meals, snacks & drinks in office
- 401k with a 100% match up to 5% of annual salary
- Regular team events
- Generous paid parental leave
- Work from home opportunities
- Health insurance
Company values
- We cultivate autonomy across the entire team by being open about our goals, wins, and challenges.
- We get to answers fast, focusing on what works—not what's fancy.
- In our field of AI and software engineering, we believe that diverse thinkers increase collective insights and knowledge.
Company HQ
Centennial, Redwood City, CA
Articles
Leadership
Alex Ratner
(Co-founder & CEO)Studied at Harvard and received a PhD from Stanford. They are also an Assistant Professor at the University of Washington.
Paroma Varma
(Co-founder)They hold a PhD from Stanford and was VP of Corporate Relations at the Society of Women Engineers. They have collaborated with teams at Facebook and Intel.
Braden Hancock
(Co-founder & Head of Technology)They have a PhD in Computer Science from Stanford, and worked as a Research Assistant with the Air Force and MIT. They were also a Software Engineer at Google, and a Researcher at Facebook.
Henry Ehrenberg
(Co-Founder)They studied at Yale and Stanford and worked at Facebook as a Quantitative Engineering Intern and a Senior Applied Research Scientist.
Salary benchmarks
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