Senior Machine Learning Engineer, Checkr

$199.4-269.8k

Python
Ruby
Pandas
Senior and Expert level
San Francisco Bay Area

2-3 days a week in office

Checkr

Automated background checks

Open for applications

Checkr

Automated background checks

1001+ employees

B2BArtificial IntelligenceEnterpriseRecruitmentHRLegalSaaSAPI

Open for applications

$199.4-269.8k

Python
Ruby
Pandas
Senior and Expert level
San Francisco Bay Area

2-3 days a week in office

1001+ employees

B2BArtificial IntelligenceEnterpriseRecruitmentHRLegalSaaSAPI

Company mission

To build a fairer future by designing technology to create opportunities for all.

Role

Who you are

  • 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 the job involves

  • 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
  • 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
  • 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

Our take

Checkr addresses the unpleasant and time consuming process of background checks so that companies using on-demand employees can make safer, more informed hiring decisions in less time. Background checks are a critical part of the hiring process, and CEO Daniel Yannisse noticed that they were painfully slow, resulting in loss of work for candidates and productivity downturns for employers.

Before Checkr entered the market in 2014 with its innovative AI technology and a solid $50m in venture capital funding, companies were waiting upwards of two weeks for their checks. Checkr substantially reduces this time frame and has grown to receive a $5 billion valuation.

Checkr has accelerated growth by making several highly advantageous acquisitions of competitor companies GoodHire and Inflection. As the world of work embraces diversity and inclusion, the company announced an end-to-end service for candidates wishing to expunge their criminal records, furthering the company’s ‘fair chance’ mission and clearing 1000s of candidates for free since 2021. New products launched at the end of 2023 include Checkr Pay (providing access to payment right after a shift) and Checkr Onboard (unified onboarding processes), exemplifying how Checkr is keeping pace with a rapidly changing, flexible, and mobile-first workforce.

Freddie headshot

Freddie

Company Specialist

Insights

Top investors

Some candidates hear
back within 2 weeks

18% employee growth in 12 months

Company

Funding (last 2 of 6 rounds)

Sep 2021

$250m

SERIES E

Sep 2019

$160m

SERIES D

Total funding: $550.2m

Company benefits

  • Parental leave
  • Stock optoins
  • Work from home opportunities
  • Comprehensive Health Plans | We cover 100% of insurance premiums and offer generous parental and family leave
  • Competitive Compensation | We offer competitive salaries and meaningful equity
  • A Variety of Food and Snacks | Our culinary team serves a rotating menu for lunch each day, along with unlimited snacks and drinks
  • Wellness Programs | We invest in the holistic well-being of every team member through education reimbursements, onsite massages, and physical therapy
  • Flexible Paid Time Off | We want you to take the time you need to relax and recharge
  • Fitness and Public Transport Reimbursement | We’ll cover your commute and help you stay active with our onsite gym or fitness provider of choice

Company values

  • Humility - We are respectful and free from arrogance. We put the success of our employees over our company and are excited to learn from each other.
  • Grit - We are passionate and hustle to raise the bar. We persevere through our challenges and grow from our failures.
  • Transparency - We trust each other to communicate the good and the bad as it relates to doing our best work. We aren’t afraid to voice our opinions and are receptive to feedback.
  • Connection - We genuinely care about each other and understand that our people are our power. We celebrate our lived experiences and enjoy helping and supporting each other.
  • Ownership - We strive for thoughtful impact, take pride in our work, and hold ourselves accountable. We step up and take on new challenges to help further the success of the company.

Company HQ

Financial District, San Francisco, CA

Leadership

After an MSc in Computer Science, Jonathan worked as a Software Engineer at Mogreet and deliv for a combined year and a half. He co-founded Checkr in May 2014, serving as CTO since.

Daniel worked as a Software Engineer at Mogreet and Deliv before co-founding Checkr.

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