Source Job

US

  • Design, deploy, and optimize large-scale ML systems for retrieval, ranking, and LLM-powered features.
  • Lead ML projects from concept to production, improving answer relevance and user experience.
  • Collaborate with Product, Data Science, and Engineering teams to shape technical direction.

Python PyTorch TensorFlow LLM RAG

20 jobs similar to Machine Learning Engineer, Answers Relevance

Jobs ranked by similarity.

US Unlimited PTO

  • Implement embeddings, vector storage, and retrieval across a large, provenance-tracked evidence base.
  • Integrate language models so generated text is bound to cited source records, and test for citation failures.
  • Own prompt and output-schema design, model packaging, versioning, serving, and rollback.

DEFCON AI is an insights company that leverages artificial intelligence, mathematical optimization, data analytics, and software engineering to build resilient optimization systems for complex operations. The company offers a fully remote, results-based environment with a focus on production systems and a strong benefits package.

$160,000–$190,000/yr
US

  • Own end-to-end ML systems from data and training to evaluation, inference, and deployment.
  • Build and evolve training, fine-tuning, and inference infrastructure for large models.
  • Partner with research and application engineering to turn model capabilities into product improvements.

Next Step Systems is an IT recruiting and staffing agency that connects companies with machine learning and technology talent. They specialize in placing candidates in remote and on-site roles across the United States and emphasize a fast-paced, results-oriented culture.

  • Own AI agents and autonomous workflows powered by LLMs from problem framing through production.
  • Build RAG pipelines, set evaluation and guardrail standards, and optimize for cost and scalability.
  • Work directly with client teams to scope problems and deploy AI systems in their environments.

Acceler is a Forward-Deployed Engineer company that takes AI from pilot to production inside client systems. With a practitioner network of nearly 1,000 engineers across the US and India, it's a high-caliber team built on ownership, trust, and rapid learning.

Mexico

  • Design, train, and deploy ML models for text classification, entity extraction, and topic detection.
  • Build LLM-powered features including RAG, prompt design, and agentic workflows.
  • Collaborate daily with US-based engineers and productionize models as monitored services.

Tech Holding is a full-service consulting firm that delivers predictable outcomes and high-quality solutions to clients from startups to Fortune 50 companies. The culture is built on deep expertise, integrity, transparency, and dependability, with a team of experienced industry professionals.

US

  • Lead the end-to-end machine learning lifecycle, from data preparation and model training to evaluation, inference, and deployment.
  • Build and optimize scalable training, fine-tuning, and inference pipelines for large-scale models on GPU infrastructure.
  • Establish production best practices for model quality, reliability, safety, and measurable performance improvements.

This company builds production-grade machine learning systems and large-scale GPU-powered inference pipelines. It is a fully remote team that values technical rigor, collaboration, and hands-on engineering.

$200,000–$280,000/yr
US Unlimited PTO

  • Design production search, ranking, and recommendation systems.
  • Build ML models end-to-end, from feature engineering to monitoring.
  • Develop LLM-powered conversational search and image-based matching with RAG.

They operate a global digital marketplace for product discovery and evaluation, powered by advanced search and AI. They support a small, high-ownership engineering team with a remote-first culture and significant autonomy.

$171,063–$269,075/yr
Global

  • Develop machine learning and LLM capabilities for query intelligence and search relevance.
  • Build agentic search planners and improve model behavior through prompt development and fine-tuning.
  • Own projects from problem definition to production deployment and collaborate with cross-functional teams.

Atlassian builds software products that help teams collaborate and manage work. The company fosters a flexible and inclusive culture, with employees able to choose where they work and a focus on innovation.

North America Unlimited PTO

  • Lead exploration and application of Large Language Models and Generative AI into core product lines.
  • Translate the latest research into high-performing systems that enhance customer experiences.
  • Collaborate with cross-functional teams to set strategy and deploy ML solutions with real business impact.

Replicant is the industry leader in voice AI for customer service, providing automated phone bots for enterprises like AAA and Fanatics. Founded in 2017, the company is backed by top-tier Silicon Valley investors, has offices in the SF Bay Area, Toronto, and New York, and maintains a distributed team across the US and Canada.

India

  • Build new functionality within a fast-moving product, taking ambiguous ideas from design to rigorous experimentation within weeks.
  • Conduct deep-dive research into state-of-the-art LLM orchestration, retrieval strategies, and data-driven personalization.
  • Build production-grade ML systems at Twilio scale, leveraging the latest AI development stacks to focus on core differentiation.

Twilio is a cloud communications platform that enables businesses to create personalized customer experiences through APIs and AI-driven solutions. The company is remote-first, serving hundreds of thousands of businesses, and fosters a culture of connection, inclusion, and innovation.

United States

  • Design and train advanced ML models (e.g., DNNs, transformers) to power Reddit Ads Ranking.
  • Develop and optimize features including embeddings, contextual signals, and cross-session behavior.
  • Mentor other MLEs and contribute to modeling best practices across the organization.

Reddit is a community of communities built on shared interests, passion, and trust. With over 100,000 active communities and approximately 130 million daily active unique visitors, it is one of the internet's largest sources of information and employs a flexible first workforce.

Global Unlimited PTO

  • Design, build, and maintain scalable real-time ML services for ranking and personalization.
  • Analyze user behavior and run A/B tests to improve product discovery and engagement.
  • Collaborate with engineers, data specialists, and business stakeholders to drive measurable outcomes.

The company is an AI-driven e-commerce platform that uses machine learning to power smarter search, discovery, and shopping experiences. It maintains a collaborative, remote-first culture that values ownership, inclusion, and meaningful impact.

Global

  • Design, build, and deploy production ML and LLM-based systems for enterprise clients.
  • Own technical delivery end-to-end from architecture to deployment and iteration.
  • Mentor and support other ML engineers through code reviews and technical guidance.

TensorOps is a boutique AI consultancy that designs and ships production-grade AI systems for enterprise clients. The company has shipped AI systems impacting 200M+ end users daily, partnered with 11 unicorns, and operates fully remotely with a supportive, fast-growing culture.

Global Unlimited PTO

  • Build and operate real search infrastructure for ranking and multi-modal search across Nivoda's marketplace.
  • Own the full lifecycle of ranking and recommendation models, from features and training through deployment and monitoring.
  • Build context-aware and conversational search using LLMs, embedding-based retrieval, and image embeddings.

Nivoda is the operating system for the global jewellery industry, connecting diamond and gemstone suppliers directly with retailers across more than 70 countries. We're a small, high-ownership team with a remote-first culture, powering over $300M in annual transactions.

  • Building multi-agent systems and implementing agent-based workflows and AI automation solutions.
  • Developing and optimizing prompt engineering strategies, including evaluation and iteration.
  • Integrating LLMs and AI models into cloud-based applications and APIs while researching new AI tools.

Software Mind develops impactful software solutions for global companies, partnering with tech giants and unicorns on transformative projects. The company builds cross-functional engineering teams and embraces a culture of openness, respect, grit, and cooperation.

Europe 6w PTO 26w maternity 26w paternity

  • Develop deep understanding of customer problems and map them to Cohere solutions as a trusted technical advisor.
  • Lead design and deployment of customer pilots, owning the technical narrative from discovery to business case.
  • Collaborate with Product and Engineering teams and partners to scale solutions and gather customer feedback.

Cohere is a leading security-first enterprise AI company building cutting-edge foundation AI models and products for real-world business problems. It is a global team of researchers, engineers, and designers headquartered in Toronto with offices worldwide, committed to driving AI adoption.

$85,000–$102,000/yr
US

  • Identify and implement AI/ML opportunities across products, including generative AI and LLM applications.
  • Build, evaluate, deploy, and maintain machine learning models in production.
  • Collaborate with product managers, engineers, and experts to translate business challenges into scalable ML solutions.

The company applies machine learning and AI to real-world business and product challenges. It fosters a collaborative, remote-first environment centered on technical learning, innovation, and professional development.

US Unlimited PTO

  • Build the component layer around our layout synthesis engine, including API contracts, services, and evaluation gates.
  • Turn model retraining into a one-command job with built-in benchmarks and readable results for the whole team.
  • Own latency and cost budgets for learned capabilities and partner with infrastructure engineers on MLOps and deployment.

Higharc is a VC-backed startup that is changing how new homes are designed and built using spatial AI and generative floor plan technology. The company is fully remote, has raised over $175M, and values flexibility, collaboration, and asynchronous deep work.

$107,360–$152,900/yr
US

  • Design, build, and deploy LLM-powered agents that detect spam, harassment, and policy-violating content on Quora.
  • Develop agentic workflows to automate content moderation and user safety tasks at scale.
  • Evaluate model performance, investigate failures, and refine AI systems for accuracy and efficiency.

Quora is a global knowledge-sharing platform that connects people with expert answers. This role sits on a small, collaborative engineering team with a remote-first culture and a focus on AI safety and content quality.

$250,000–$250,000/yr
US

  • Lead technical design and architecture for Medium's ML recommendation backend.
  • Build and scale feature store, recommender systems, and ML Ops.
  • Mentor engineers and drive cross-functional technical direction.

Medium is an online publishing platform that connects millions of readers with ideas and stories. The company values engineering excellence, collaboration, and a culture of mentorship and continuous improvement.

US

  • Lead end-to-end delivery of complex healthcare AI products, including agentic workflows, RAG systems, and production services.
  • Collaborate with Product, Engineering, Data, and clinical teams to translate stakeholder needs into validated, access-aware AI workflows.
  • Own evaluation frameworks, model optimization, and human-review controls to keep high-stakes workflows safe, reliable, and governable.

NeueHealth is a value-driven healthcare company that aligns the interests of health consumers, providers, and payors to make healthcare accessible and affordable. They deliver clinical care through owned clinics and provider partnerships while enabling performance-based care with technology and services.