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The job board for developers. Find your next role at companies that value great engineering.

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15 matches
NewestHighest base
Hang

Machine Learning Engineer

today
Hang · New York, NY
RemoteFull-timePython · TensorFlow
Epistemix

AI Engineer

today
Epistemix · US; CA; UK
RemoteFull-timePython · FastAPI
Emergence Capital Partners

Staff Software Engineer, Applied AI

today
Emergence Capital Partners · San Francisco, CA
On-siteFull-timePython · TypeScript
Blank Metal

AI Engineer

today
Blank Metal · Minneapolis, MN
On-siteFull-timePython · React
Klue

Senior Software Engineer, AI

today
Klue · Toronto, ON
HybridFull-timePython · PyTorch
OuterSignal

Senior Software Engineer

today
OuterSignal · New York, NY
$200k–300kOn-siteFull-timeTypeScript · Node.js
Fabrion

ML/AI Research Engineer — Agentic AI Lab (Founding Team)

today
Fabrion · San Francisco, CA
On-siteFull-timePython · HuggingFace Transformers
Higharc

Research Engineer

today
Higharc · Remote (United States)
RemoteFull-timePython · PyTorch
Nuclear Promise X

Software Developer Intern

today
Nuclear Promise X · Ontario
$54k–64kRemoteContractReact · Next.js
Nuclear Promise X

Senior AI Developer (Coming Soon!)

today
Nuclear Promise X · Canada
$130k–160kRemoteFull-timePython · React
webAI

AI Software Engineer

today
webAI · Austin, TX
On-siteFull-timeC++ · Python
Rula

Principal AI Engineer - Personalization and Recommendation (Remote)

today
Rula · Remote - United States
$282k–371kRemoteFull-timePython · TypeScript
Seven AI

Senior AI Engineer

today
Seven AI · Boston, MA
$165k–230kOn-siteFull-timePython · LangChain
WRITER

Software engineer, generative AI

today
WRITER · San Francisco, CA
$132k–240kHybridFull-timePython · FastAPI
Camunda

Senior GTM Systems AI and Automation Engineer

today
Camunda · Remote
$144k–232kRemoteFull-timePython · TypeScript
Hang

Machine Learning Engineer

Hang · 🇺🇸 New York, NY · posted today
ApplyFull posting

Extracted from the posting

Base
Not stated
Remote
Remote
Funding
$16M Series A led by Paradigm
Stack
Python, TensorFlow, PyTorch, PostgreSQL

TL;DR

Machine Learning Engineer role to design, build, and deploy ML models for personalization, predictive analytics, and automated decision-making. Requires Python, TensorFlow or PyTorch, vector databases, LLM deployment in production, and AWS, Postgres, Redis, and Snowflake experience. Ruby experience is a plus; 5+ years in ML or data roles required.

About Hang →

The full posting

Hang is building the future of loyalty for brands.

Hang is the next generation brand loyalty & membership platform. By harnessing the power of personalization, gamification, and its integrations ecosystem, Hang provides brands with a radically new type of loyalty experience for their customers.

Today, they work with a variety of major brands (such as Ulta Beauty, Budweiser, Flipkart, and more), as well as multiple well-known, up-and-coming restaurant chains (Boba Guys, Roam Artisan Burger, and Williamsburg Pizza, among several others).

Hang draws from years of deep expertise in loyalty, game design, and finance with employees from leading companies like Google, Amazon, Apple, Meta, LinkedIn, Coinbase, Square, and Goldman Sachs.

Hang raised a $16 million Series A led by Paradigm last summer, with participation from Tiger Global, Howard Schultz, Kevin Durant, Mr. Beast, and the founders of Warby Parker, Allbirds, and Bombas, among others.


About the Role

We are seeking a skilled and innovative Machine Learning Engineer to join our team. This person will implement and develop machine learning models to enhance our platform's capabilities, making key contributions to our product development, and driving data-driven decision-making.


What You’ll Do

  • Model Development: Design, build, and deploy machine learning models to improve various aspects of our platform, including customer personalization, predictive analytics, and automated decision-making.
  • Data Analysis: Analyze large datasets to identify trends and patterns, and use this information to inform model development and business strategies.
  • Algorithm Optimization: Continuously test and refine algorithms to improve accuracy and efficiency.
  • Collaborative Development: Work closely with software engineers, data scientists, and product managers to integrate ML models into our platform and ensure seamless deployment.
  • Research and Innovation: Stay up-to-date with the latest developments in machine learning and AI, and explore new techniques and technologies that could benefit Hang.
  • Technical Leadership: Provide insights and guidance on best practices in machine learning, and contribute to the strategic direction of our technology.

Who You Are

  • Bachelor's or Master’s degree in Computer Science, Engineering, Mathematics, or a related field. A Ph.D. is a plus.
  • 5+ years of experience in machine learning and data related roles.
  • Proven experience as a Machine Learning Engineer or in a similar role.
  • Strong programming skills in Python and familiarity with ML frameworks (like TensorFlow or PyTorch).
  • Experience with data processing and data analytics.
  • Experience with vector databases, demonstrating proficiency in managing and querying high-dimensional data. Familiarity with popular vector databases like Redis, Milvus, Pinecone, Weaviate, Chroma or Faiss is required.
  • Knowledge of machine learning techniques and algorithms, including fine tuning processes and methodology.
  • Experience in deploying Large Language Models (LLMs) in production environments, including optimization and scaling considerations.
  • Experience with snowflake, Postgres, RDS, Redis and AWS.
  • Excellent problem-solving skills and ability to work in a fast-paced environment.
  • Strong communication skills and ability to work well in a team.
  • Experience with Ruby is a plus.
  • What Would Set You Apart

    • You have a passion for consumer brands and loyalty programs.


    Benefits

    • Top-tier health, vision, and dental insurance, including plans with $0 employee cost.
    • Unlimited PTO / sick leave
    • Competitive salary & equity compensation.
    • Quarterly company offsites