About the role

As a Senior ML Engineer on the ML/Applied Scientist Team at Checkr, you will be responsible for building and managing several ML/AI algorithms, processes, and tools that Product Engineering teams rely on to deliver Checkr’s products and features. You will work closely with engineering and product teams to help them implement the best algorithms and processes at scale in their services.

What you’ll do

• Develop Cutting-Edge ML/AI Solutions: Collaborate closely with product and engineering teams to design, develop, and deploy innovative ML/AI models and algorithms. These solutions will target enhancing gross margin efficiency and optimizing our background check processes.
• Integrate ML/AI in Products: Partner with product teams to embed and scale ML/AI capabilities within our external product offerings, ensuring state-of-the-art technology is seamlessly integrated to provide tangible value to our users.
• Data Analysis and Feature Engineering: Conduct thorough data analysis, identify key features, and preprocess data to create robust and scalable ML models that drive process improvements.
• Model Evaluation and Optimization: Evaluate the performance of machine learning models, iterating and optimizing them for accuracy, efficiency, and scalability.
• Cross-Functional Collaboration: Work in tandem with various stakeholders, including data scientists, software developers, and product managers, to understand business requirements and translate them into technical solutions.
• Stay Ahead of Industry Trends: Keep abreast of the latest advancements in machine learning, artificial intelligence, and related fields, championing innovation and applying cutting-edge techniques to solve complex problems.
• Mentorship and Leadership: Provide guidance and mentorship to junior engineers within the team, fostering a culture of continuous learning and improvement.

What a typical week may look like at Checkr

• Data-driven analysis: Use data analysis to drive and vet future initiatives, ensuring that our strategies are backed by solid evidence.
• Automated decision-making tools: Develop tools to automate decision-making, reducing manual effort and improving response times.
• Enhance customer and applicant experience: Build and deploy ML/AI models that enhance the experience for both customers and applicants, contributing to a more streamlined process.
• Classification of Charges: Work on classifying charges into different categories using advanced ML techniques to improve the accuracy and reliability of background checks.
• AI Capabilities for Document Processing: Integrate AI capabilities to automate and enhance document processing tasks, reducing manual effort and improving accuracy.
• In-product ML/AI: Build machine learning models for in-product features, such as personalized recommendations, to improve user engagement and satisfaction.
• Integration interfaces: Implement robust interfaces to allow seamless integration with our platform, ensuring our ML/AI models can be easily utilized.

What you bring

• Industry experience: 7+ years, especially in roles focused on machine learning.
• Regression-based problem-solving: Proven ability to solve regression-based problems, enhancing business insights and operational efficiency.
• Production-ready NLP systems: Experience building NLP systems that are ready for production, demonstrating expertise in natural language processing.
• Distributed systems: A solid background in working with distributed systems, ensuring scalability and reliability of solutions.
• Programming skills: Proficiency in Ruby or Python, enabling seamless implementation and integration of your solutions.
• ML frameworks: Hands-on experience with building and designing experiments to evaluate different ML/AI algorithms (including deep learning).
• GenAI - Knowledge of generative AI, fine tuning and AI design patterns is a plus.
• Data manipulation and analysis: Proficiency with Pandas and sci-kit learn, essential for data preprocessing and model evaluation.
• Educational background: BSc, MSc, or PhD in Computer Science, Mathematics, or a related technical field, providing a strong foundation in technical knowledge and problem-solving skills.

What you’ll get

• A fast-paced and collaborative environment
• Learning and development allowance
• Competitive compensation and opportunity for advancement
• 100% medical, dental, and vision coverage
• Up to $25K reimbursement for fertility, adoption, and parental planning services
• Flexible PTO policy
• Monthly wellness stipend, home office stipend
• Catered Lunch and snacks

At Checkr, we believe a hybrid work environment strengthens collaboration, drives innovation, and encourages connection. Our hub locations are Denver, CO, San Francisco, CA, and Santiago, Chile. Individuals are expected to work from the office 2 to 3 days a week. In-office perks are provided, such as lunch four times a week, a commuter stipend, and an abundance of snacks and beverages.

One of Checkr’s core values is Transparency. To live by that value, we’ve made the decision to disclose salary ranges in all of our job postings. We use geographic cost of labor as an input to develop ranges for our roles and as such, each location where we hire may have a different range. If this role is remote, we have listed the top to the bottom of the possible range, but we will specify the target range for an exact location when you are selected for a recruiting discussion. For more information on our compensation philosophy, see our website.

The base salary range for this role is $199,441 to $269,833 in San Francisco, CA.

Equal Employment Opportunities at Checkr

Checkr is committed to hiring talented and qualified individuals with diverse backgrounds for all of its tech, non-tech, and leadership roles. Checkr believes that the gathering and celebration of unique backgrounds, qualities, and cultures enriches the workplace.

Checkr also welcomes the opportunity to consider qualified applicants with prior arrest or conviction records. Checkr’s commitment to diversity extends to hiring talented individuals in spite of a prior criminal history in accordance with local, state, and/or federal laws, including the San Francisco’s Fair Chance Ordinance.