Job Details

Machine Learning Engineer

  2025-09-08     Two Dots     San Francisco,CA  
Description:

Overview

Two Dots provided pay range. This range is provided by Two Dots. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

$150,000.00/yr - $225,000.00/yr

Join Two Dots to build a stronger financial system.

Every time someone applies for a mortgage, car loan, or apartment lease, they submit financial documents that humans use to build a financial profile about them. The quality of these financial profiles is a key input that regulates the body temperature of the economy. Two Dots is building a better system to evaluate consumers consistently and fairly. We prevent fraud that humans can't see, and we surface value in atypical applications that would otherwise be discarded.

Please note that we require all full-time employees to work from our office in San Francisco, CA.

Role overview

Reporting directly to our Co-Founder and CTO, Two Dots is looking for our first-ever Machine Learning Engineer. In this role you will design, develop, and deploy machine learning solutions, with a focus on fine tuning multimodal large language models (LLMs) to solve real-world problems. The ideal candidate will have a passion for building and deploying advanced ML applications, with the aim to produce business impact and client satisfaction.

Key Responsibilities

  • Work autonomously to design, develop and deploy machine learning models
  • Analyze large datasets to uncover insights and trends that inform product development and personalized customer experiences
  • Continuously monitor and improve the performance of deployed models, ensuring they meet business objectives and scalability requirements
  • Stay up to date with the latest advancements in machine learning, AI, data science and engineering, and apply this knowledge to improve our products and services

Qualifications (Desirable Traits)

  • 2+ years of experience in a Machine Learning or Data Engineering role, with a strong proficiency in Python and ML frameworks like PyTorch required
  • Proven ability to improve models for key information extraction, including named entity recognition and matching, and financial document classification
  • Experience with active learning, HITL driven workflows; working with large labeling and quality teams is a plus
  • Strong problem solving skills, with the ability to think critically and creatively
  • Excellent communication and interpersonal skills, capable of explaining complex operational information in an understandable way
  • A proactive, curious mindset with a relentless pursuit of excellence and innovation in tackling complex problems
  • Hungry for personal and professional growth and ready to scale with Two Dots

What you get in return

  • An opportunity to revolutionize the real estate leasing industry and own projects that make a tangible impact
  • An environment with a work culture that is based on trust, ownership, flexibility and a growth mindset
  • A competitive salary, comprehensive equity package, and substantial benefits

Closing

Two Dots is an equal opportunity employer. We aim to build a workforce of individuals from different backgrounds, with different abilities, identities, and mindsets. Even if you do not meet all of the qualifications listed above, we encourage you to apply!

Compensation is variable and is subject to a candidate's personal qualifications and expectations. For this role, we offer the following base salary range, in addition to an equity package and full benefits: $150k - $225k per year.

Compensation Range: $150K - $225K

Seniority level

  • Entry level

Employment type

  • Full-time

Job function

  • Engineering and Information Technology

Industries

  • Software Development

Referrals increase your chances of interviewing at Two Dots by 2x

We're unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.

#J-18808-Ljbffr


Apply for this Job

Please use the APPLY HERE link below to view additional details and application instructions.

Apply Here

Back to Search