Two Dots Logo

Two Dots

Machine Learning Engineer

Reposted 16 Days Ago
In-Office
San Francisco, CA, USA
150K-250K Annually
Mid level
In-Office
San Francisco, CA, USA
150K-250K Annually
Mid level
The Machine Learning Engineer will develop and deploy ML solutions, analyze data for insights, and monitor model performance to enhance products.
The summary above was generated by AI

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: 

Two Dots is looking for our 2nd Machine Learning Engineer, who will work closely with the CTO and the Staff ML 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 by increasing our application approval/denial automation rate and increasing our fraud detection capabilities.

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

Desirable Traits

  • 3+ 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 a large equity package and full benefits): $175k - $250+k per year.

HQ

Two Dots San Francisco, California, USA Office

San Francisco, CA, United States

Similar Jobs

16 Hours Ago
Remote or Hybrid
Sunnyvale, CA, USA
171K-261K Annually
Senior level
171K-261K Annually
Senior level
Automotive • Big Data • Information Technology • Robotics • Software • Transportation • Manufacturing
The role involves building user experiences, automating ML workflows, applying ML to data labeling, and collaborating across teams to improve data quality for autonomous vehicles.
Top Skills: GoGraphQLPythonReactReduxSQLTypescriptWebgl
Yesterday
Hybrid
Mountain View, CA, USA
Mid level
Mid level
Artificial Intelligence • Cloud • HR Tech • Information Technology • Productivity • Software • Automation
The Machine Learning Engineer will improve enterprise search systems using traditional machine learning and generative AI, collaborating with various teams to enhance the platform's capabilities.
Top Skills: Generative AiGoInformation RetrievalLarge Language ModelsNatural Language UnderstandingPython
Yesterday
Hybrid
2 Locations
147K-259K Annually
Mid level
147K-259K Annually
Mid level
Artificial Intelligence • Cloud • Machine Learning • Mobile • Software • Virtual Reality • App development
As a Machine Learning Engineer on the Ads Platform team, you'll design and develop ML models for ad ranking and delivery, improve efficiency and relevance, and collaborate with cross-functional partners.
Top Skills: Caffe2Machine LearningPyTorchScikit-LearnSpark MlTensorFlow

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account