Role in brief
Checkr is seeking a Machine Learning Engineer to develop and deploy ML/AI services, focusing on model design, API integration, and production deployment. This role involves close collaboration with product and engineering teams. Candidates with strong Python skills, experience with LLM APIs, and a background in building production ML systems should consider applying.
About the role
This role involves the full lifecycle of machine learning and AI services, from initial design to production deployment. The engineer will be responsible for creating ML models, developing the necessary API layers, implementing monitoring solutions, and writing comprehensive tests. A key part of the work includes designing with Large Language Models (LLMs) and their APIs, ensuring that AI-powered workflows are shipped effectively.
The position requires a professional with at least four years of software development experience, including a minimum of two years dedicated to building ML systems for production environments. Success in this role means consistently delivering robust, production-ready ML/AI solutions that product engineering teams can rely on. The ability to iterate quickly and evaluate solutions is also crucial.
The team operates in a fast-paced and collaborative setting, emphasizing innovative ML/AI solutions. The engineer will partner closely with product and engineering colleagues to integrate AI capabilities into various offerings. This environment supports continuous learning and development, with opportunities for career advancement within the company.
The compensation for this role ranges from $100,000 to $150,000 annually, in addition to competitive equity compensation.
Skills that matter here
- Python: Fluency in Python is essential for writing clean, testable, and well-structured code with strong object-oriented programming principles.
- ML systems: The role requires at least two years of experience building machine learning systems that operate in a production environment.
- LLM APIs: Hands-on experience using Large Language Model APIs in production systems is a key requirement for designing and implementing AI solutions.
- CI/CD: Experience with CI/CD pipelines is necessary for shipping code and maintaining APIs that other engineers depend on.
- NLP: Experience with Natural Language Processing tasks in production is relevant for developing specific AI-powered workflows.
- distributed systems: Comfort with distributed systems concepts is important for building scalable and robust ML/AI services.
Who this role suits
- A person who thrives on building and deploying production-ready machine learning and AI services.
- Someone with a strong bias for action and a mindset focused on high performance.
- An individual who enjoys collaborating with product and engineering teams to integrate AI solutions.
- A professional who values continuous learning and is comfortable with fast iteration and evaluation cycles.
From the employer
What you’ll do
- Build and deploy ML/AI services.
- Design, develop, and ship ML models and AI systems that Product Engineering teams rely on.
- Write the model code, the API layer, the monitoring, and the tests.
- Design with LLMs and APIs.
- Ship production software.
- Partner with product and engineering.
- Evaluate and iterate fast.
- Ship AI-powered workflows.
What you bring
- A Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related technical field, or equivalent depth from experience.
- 4+ years building software professionally, with at least 2 of those building ML systems that run in production.
- Strong Python fluency; you write clean, testable, well-structured code with solid OOP instincts.
- Hands-on experience using LLM APIs in production systems.
- You’ve built and maintained APIs, worked with CI/CD pipelines, and shipped code that other engineers depend on.
- Comfortable with distributed systems concepts.
- Experience with NLP tasks in production.
- Strong communication skills.
- An A-player mindset with a strong bias for action.
What we offer
- A fast-paced and collaborative environment.
- Learning and development allowance.
- Competitive cash and equity 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.
- In-office perks and hub locations with in-office presence required 3+ days a week.
- A relocation stipend may be available.
Questions about this role
What is the company's remote work policy?
This is a remote position, but an in-office presence is required 3+ days a week at hub locations. A relocation stipend may be available.
What is the required seniority level for this role?
This is a middle-seniority position, requiring 4+ years of professional software building experience with at least 2 years in production ML systems.
What are the key technical skills required?
Key technical skills include strong Python fluency, experience with ML systems in production, hands-on experience with LLM APIs, CI/CD, NLP, and distributed systems concepts.
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