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Machine Learning Engineer Llm Jobs (NOW HIRING)

Reddit

Senior Machine Learning Engineer

$107K - $146K/yr

We hire Machine Learning Engineers across both our Consumer and Ads organizations, giving you the ... Applied AI and LLM-driven experiences that improve relevance, discovery, and user engagement You'll ...

Five and Fly

Machine Learning Engineer

Atlanta, GA · On-site

Machine Learning Engineer Employment Type: Full Time Location: Atlanta, GA Description We are ... Work hands-on with multiple LLM ecosystems: * OpenAI GPT models (GPT-4, GPT-4o, fine-tuned GPTs)

Accelint

Machine Learning Engineer

We are seeking an experienced Machine Learning Engineer / NLP Engineer to develop intelligent ... Build and optimize LLM-powered applications using transformer-based models, including fine-tuning ...

Reddit

Senior Machine Learning Engineer

$107K - $146K/yr

We hire Machine Learning Engineers across both our Consumer and Ads organizations, giving you the ... Applied AI and LLM-driven experiences that improve relevance, discovery, and user engagement You'll ...

S27a

Machine Learning Engineer

San Francisco, CA · On-site

$150 - $200/hr

... and LLM based planning and tool use, and translate it into practical enterprise solutions ... machine learning systems to ensure continuous improvement. * Collaborate with software engineers ...

Apple

Machine Learning Engineer

Pittsburgh, PA

As a Machine Learning Engineer in the Machine Intelligence Neural Design (MIND) team, you'll have ... Strong foundation in machine learning, and more specifically in LLM and multimodal foundation ...

UNAVAILABLE

Machine Learning Engineer

Frisco, TX · On-site

$150 - $200/hr

Overview Quarterhill is seeking a Machine Learning Engineer to join our forward-thinking team ... Experience building and deploying LLM-based systems and Retrieval‑Augmented Generation (RAG ...

S27a

$150 - $200/hr

... and LLM based planning and tool use, and translate it into practical enterprise solutions ... machine learning systems to ensure continuous improvement. * Collaborate with software engineers ...

Plenful

Machine Learning Engineer

San Francisco, CA · On-site

About the Role We're looking for a Machine Learning Engineer to design, build, and deploy ... Build intelligent services using modern NLP, LLM, classification, recommendation, and prediction ...

RXinsider LTD.

$150 - $200/hr

About The Role We're looking for a Machine Learning Engineer to design, build, and deploy ... Build intelligent services using modern NLP, LLM, classification, recommendation, and prediction ...

BigHat

$150 - $200/hr

Machine Learning Engineer Department: DS/ML (Data Science/Machine Learning) Employment Type ... Develop, refine, and deploy agentic and LLM-driven optimization methods to further automate and ...

BigHat

Machine Learning Engineer

San Mateo, CA · On-site

$150 - $200/hr

Machine Learning Engineer Department: DS/ML (Data Science/Machine Learning) Employment Type ... Develop, refine, and deploy agentic and LLM-driven optimization methods to further automate and ...

BigHat Biosciences

Machine Learning Engineer

San Mateo, CA · On-site

$150K - $200K/yr

Machine Learning Engineer Department: DS/ML (Data Science/Machine Learning) Employment Type ... Develop, refine, and deploy agentic and LLM-driven optimization methods to further automate and ...

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Machine Learning Engineer Llm information

See salary details

$31.5K

$128.8K

$193.5K

How much do machine learning engineer llm jobs pay per year?

As of Sep 9, 2026, the average yearly pay for machine learning engineer llm in the United States is $128,769.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $155,000.00 per year, depending on experience, location, and employer.

What is a machine learning engineer LLM?

Machine Learning Engineers (LLM) are professionals who design, build, and deploy large language models (LLMs) such as GPT or BERT. They combine software engineering skills with a deep understanding of machine learning algorithms to develop systems that can process and generate human-like text. Their responsibilities often include data preprocessing, model training, fine-tuning, evaluation, and integrating these models into applications. They also work to optimize performance, ensure scalability, and address ethical considerations related to AI language models.

What are common challenges machine learning engineers face when working with large language models (LLMs) in a production environment?

Machine Learning Engineers working with LLMs often encounter challenges such as optimizing model performance while managing resource constraints like memory and compute power. Additionally, ensuring data privacy and compliance can be complex due to the vast amounts of training data involved. Another common challenge is deploying and monitoring LLMs to maintain accuracy and minimize bias, requiring close collaboration with data scientists, DevOps, and product teams. Regularly updating models to reflect new data and user feedback is also crucial for maintaining relevance and performance in real-world applications.

What are the key skills and qualifications needed to thrive as a machine learning engineer LLM?

To thrive as a Machine Learning Engineer specializing in large language models (LLMs), you need a strong background in computer science, mathematics, and deep learning, typically supported by a relevant degree and experience with NLP techniques. Familiarity with frameworks like TensorFlow, PyTorch, Hugging Face Transformers, and experience working with large-scale data sets and distributed systems are essential, along with knowledge of cloud platforms such as AWS or GCP. Strong problem-solving, collaboration, and communication skills help you translate complex research into practical applications and work effectively with cross-functional teams. These combined skills ensure the ability to develop, fine-tune, and deploy LLMs that deliver real-world value while staying at the forefront of AI advancements.

What is the difference between Machine Learning Engineer Llm vs Data Scientist?

AspectMachine Learning Engineer LlmData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related; experience with ML frameworksBachelor's or Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops, tests, and deploys ML models, often in AI-focused teamsAnalyzes data, builds models, and provides insights for decision-making
Industry UsageUsed in AI product development, NLP, LLMs, and automationApplied across finance, healthcare, marketing, and research

While both roles require strong technical skills and knowledge of machine learning, Machine Learning Engineer Llm focuses on developing and deploying large language models, especially in AI applications. Data Scientists analyze data and build models for insights. The roles often overlap but differ mainly in their focus on deployment versus analysis.

What are popular job titles related to Machine Learning Engineer Llm jobs?

For Machine Learning Engineer Llm jobs, the most frequently searched job titles are:

Infographic showing various Machine Learning Engineer Llm job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 74% Full Time, 23% Part Time, and 1% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution, with an average salary of $128,769 per year, or $61.9 per hour.

Senior Machine Learning Engineer

Remote

Reddit
See more jobs at Redditexternal

$107K - $146K/yr

Full-time

Medical, Retirement, PTO

Re-posted 4 days ago

Job description

At Reddit, machine learning sits at the heart of how millions of people discover, connect, and engage with the world's largest collection of human conversations. From powering personalized recommendations and search to optimizing advertising systems and marketplace dynamics, our ML engineers tackle some of the most interesting and impactful problems in large-scale applied machine learning.

We hire Machine Learning Engineers across both our Consumer and Ads organizations, giving you the opportunity to work on a wide range of high-impact problems across the Reddit ecosystem.

We are looking for Machine Learning Engineers who are excited to build systems end-to-end, from research and modeling to production deployment, - and who want to help shape the future of discovery, relevance, and monetization at Reddit.

If you love working on complex, real-world ML problems at massive scale, this role is for you.

What You'll Work On

As a Machine Learning Engineer at Reddit, you will design and build production ML systems that power core experiences across the platform, including:

  • Personalized recommendations, search, and ranking systems that help users discover the most relevant content and communities
  • Intelligent advertising systems including ranking, bidding, measurement, and optimization
  • Content, Advertisers, and User understanding, from building foundational content/user representations to deriving insightful signals
  • Large-scale machine learning pipelines, model serving infrastructure, and real-time decision systems
  • Applied AI and LLM-driven experiences that improve relevance, discovery, and user engagement

You'll work on high-impact systems that operate at internet scale and directly influence user experience, advertiser value, and business outcomes.

What You'll Do

  • Design, build, and deploy production-grade machine learning models and systems at scale
  • Own the full ML lifecycle: from problem definition and feature engineering to training, evaluation, deployment, and monitoring
  • Build scalable data and model pipelines with strong reliability, observability, and automated retraining
  • Work with large-scale datasets to improve ranking, recommendations, search relevance, prediction, content/user understanding, and optimization systems. 
  • Partner cross-functionally with Product, Data Science, Infrastructure, and Engineering teams to translate complex problems into ML solutions
  • Improve system performance across latency, throughput, and model quality metrics
  • Research and apply state-of-the-art machine learning and AI techniques, including deep learning, graph & transformers based, and LLM evaluation/alignment 
  • Contribute to technical strategy, architecture, and long-term ML roadmap

Basic Qualifications

  • 3-5+ years of experience building, deploying, and operating machine learning systems in production
  • Strong programming skills in Python, Java, Go, or similar languages, with solid software engineering fundamentals
  • ML Fundamentals: a strong grasp of algorithms, from classic statistical learning (XGBoost, Random Forests, regressions) to DL architectures (Transformers, CNNs, GNNs)
  • Hands-on experience with modern ML frameworks (e.g., PyTorch, TensorFlow)
  • Experience designing scalable ML pipelines, data processing systems, and model serving infrastructure
  • Ability to work cross-functionally and translate ambiguous product or business problems into technical solutions
  • Experience improving measurable metrics through applied machine learning

Preferred Qualifications

  • Experience with recommender systems, search/ranking systems, advertising/auction systems, large-scale representation learning, or multimodal embedding systems
  • Familiarity with distributed systems and large-scale data processing (Spark, Kafka, Ray, Airflow, BigQuery, Redis, etc.)
  • Experience working with real-time systems and low-latency production environments
  • Background in feature engineering, model optimization, and production monitoring
  • Experience with LLM/Gen AI techniques, including but not limited to LLM evaluation, alignment, fine-tuning, knowledge distillation, RAG/agentic systems and productionizing LLM-powered products at scale
  • Advanced degree in Computer Science, Machine Learning, or related quantitative field

Potential Teams

  • Ads Measurement Modeling 
  • Ads Targeting and Retrieval
  • Advertiser Optimization
  • Ads Marketplace Quality
  • Ads Creative Effectiveness
  • Ads Foundational Representations
  • Ads Content Understanding
  • Ads Ranking
  • Feed Relevance
  • Search and Answers Relevance
  • ML Understanding
  • Notifications Relevance

Benefits

  • Comprehensive Healthcare Benefits and Income Replacement Programs
  • 401k with Employer Match
  • Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
  • Family Planning Support
  • Gender-Affirming Care
  • Mental Health & Coaching Benefits
  • Flexible Vacation & Paid Volunteer Time Off
  • Generous Paid Parental Leave 

Apply