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Flexible Llm Training Jobs (NOW HIRING)

Good Start Labs

RESEARCH SCIENTIST

Manhattan, NY · On-site

$125 - $150/hr

Published research in RL, multi-agent systems, or LLM training * Strong Python and PyTorch/JAX ... Toronto or New York preferred; flexible for exceptional remote candidates * Partnerships : Direct ...

Sciforium

GPU Kernel Engineer

San Francisco, CA · On-site

$200 - $250/hr

Experience working with large-scale LLM workloads (training or inference). Nice-to-Haves ... Flexible time off * Competitive salary and equity Equal opportunity Sciforium is an equal ...

4MindsAI Inc.

Forward Deployed Engineer

Dallas, TX · On-site +1

$190K - $225K/yr

You'll work directly with enterprise clients to deploy, debug, and optimize 4MINDS LLM training ... Flexible Spending Account (FSA) and Health Savings Account (HSA) options. Professional Development

Sciforium

$200 - $250/hr

Experience working with large-scale LLM workloads (training or inference). Nice-to-Haves ... Flexible time off * Competitive salary and equity Equal opportunity Sciforium is an equal ...

4MindsAI Inc.

Forward Deployed Engineer

Dallas, TX · On-site +1

$190K - $225K/yr

You'll work directly with enterprise clients to deploy, debug, and optimize 4MINDS LLM training ... Flexible Spending Account (FSA) and Health Savings Account (HSA) options. Professional Development

Gap International

AI/LLM Engineer

Springfield, PA · On-site

Experience designing and implementing end-to-end training pipelines, including data shaping, model ... Curious and flexible when it comes to their own growth and development, as well as receptive to ...

Gap International

AI/LLM Engineer

Springfield, PA · On-site

Experience designing and implementing end-to-end training pipelines, including data shaping, model ... Curious and flexible when it comes to their own growth and development, as well as receptive to ...

Gap International

AI/LLM Engineer

Philadelphia, PA · On-site

Experience designing and implementing end-to-end training pipelines, including data shaping, model ... Curious and flexible when it comes to their own growth and development, as well as receptive to ...

UBS

Gen-AI Data Scientist Lead

New York, NY · On-site

... and flexible working options when possible. Our inclusive culture brings out the best in our ... LLM training and fine-tuning techniques such as PEFT, LoRA, quantization, RLHF, and DPO • ...

Alumni Ventures

Applied Scientist (ML)

Mountain View, CA · On-site

$200 - $250/hr

Familiarity with retrieval‑augmented generation, reasoning, LLM training and reinforcement ... Access comprehensive health insurance, including medical, dental, vision, flexible spending account ...

Public Storage

Generative AI/LLM Engineer

Frisco, TX · On-site

MLOps experience with continuous training and deployment workflows. * Frontend development skills ... flexible remote days per month. Public Storage is an equal opportunity employer and embraces ...

Public Storage

Generative AI/LLM Engineer

Frisco, TX · On-site

MLOps experience with continuous training and deployment workflows. * Frontend development skills ... flexible remote days per month. Public Storage is an equal opportunity employer and embraces ...

Public Storage

Generative AI/LLM Engineer

Frisco, TX · On-site

MLOps experience with continuous training and deployment workflows. * Frontend development skills ... flexible remote days per month. Public Storage is an equal opportunity employer and embraces ...

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Flexible Llm Training information

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How much do flexible llm training jobs pay per year?

As of Sep 8, 2026, the average yearly pay for flexible llm training in the United States is $77,988.00, according to ZipRecruiter salary data. Most workers in this role earn between $64,000.00 and $89,500.00 per year, depending on experience, location, and employer.

What is flexible LLM training?

Flexible LLM (Large Language Model) Training refers to customizable and adaptable methods for training AI models, particularly large language models, to suit specific needs or constraints. This approach allows users to adjust training parameters, data sources, and model architectures, making it easier to optimize models for different tasks, hardware, or data availability. Flexible LLM training is useful for organizations wanting to fine-tune models for specialized domains or improve efficiency in resource-limited environments.

What are the key skills and qualifications needed to thrive in flexible LLM training?

To excel as a Flexible LLM Training Specialist, you generally need a strong background in machine learning, natural language processing, and data engineering, often supported by an advanced degree in computer science or a related field. Familiarity with deep learning frameworks such as PyTorch or TensorFlow, experience with distributed training systems, and knowledge of cloud computing platforms are typically required. Critical thinking, problem-solving, and adaptability are vital soft skills, as well as strong collaboration and communication abilities. These competencies ensure effective model development, efficient troubleshooting, and successful deployment of large language models in dynamic environments.

What are common challenges in flexible LLM training, and how can they be managed?

Professionals in flexible LLM training roles often encounter challenges such as managing diverse data sources, adapting to rapidly evolving model architectures, and ensuring efficient use of computational resources. Balancing experimentation with reproducibility and collaborating across interdisciplinary teams can also be demanding. To address these challenges, it's important to implement robust workflow automation, stay updated on new research, and foster open communication with data engineers and machine learning specialists. Leveraging cloud-based tools and adhering to best practices in documentation can further streamline the training process.

What is the difference between Flexible Llm Training vs Data Scientist?

AspectFlexible Llm TrainingData Scientist
Required CredentialsTypically requires knowledge of machine learning, NLP, and programming skillsRequires degrees in statistics, computer science, or related fields, often with programming skills
Work EnvironmentOften involves training models in cloud or research labs, collaborative teamsData analysis, modeling, and visualization in corporate or research settings
Industry UsageUsed in AI development, NLP projects, and machine learning researchApplied across industries for data analysis, predictive modeling, and decision-making

Flexible Llm Training focuses on developing and fine-tuning language models, requiring technical skills in machine learning and NLP. Data Scientists analyze data, build models, and generate insights. While both roles involve data and programming, Flexible Llm Training is specialized in AI model training, whereas Data Scientists have broader data analysis responsibilities.

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Flexible Llm Training jobs near you
Infographic showing various Flexible Llm Training job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 18% Part Time, and 1% Contract. Highlights an 92% Physical, 1% Hybrid, and 7% Remote job distribution, with an average salary of $77,988 per year, or $37.5 per hour.

RESEARCH SCIENTIST

Good Start Labs

Manhattan, NY • On-site

$125 - $150/hr

Other

Posted 20 days ago

Job description

Good Start Labs builds games that make AI models better, for us. We're defining the category of alignment through entertainment.

We need a Research Scientist to help design and execute research that improves language models through game-based training. You'll work on improving a 260B+ parameter model we have under contract by EOY, using RL environments and game-generated data to demonstrate measurable capability improvements.

Our agents are integrated into games with millions of players, we have live contracts with model training labs, and our research was just accepted to the NeurIPS workshop on multi-turn interactions in LLMs (submitted to AAAI). We're backed by General Catalyst and Inovia, with advisors including Kelly Clancy (ex-DeepMind, author of Playing With Reality) and researchers from major AI labs like Anthropic.

What You'll Do
  • Help design research experiments exploring how games improve model capabilities—initially focused on agents and computer use
  • Build and optimize RL environments, curate pre-training data, implement training algorithms, run large-scale experiments
  • Work on improving a 260B+ parameter model using game-generated data and RL techniques (pre-training and post-training)
  • Collaborate with university research partners at Princeton, Rice, UCSD, HKUST, UMD, and NYU on experiments and publications
  • Demonstrate measurable model improvements to our lab partners
Who You Are

Required:

  • PhD in CS, ML, or related field (or equivalent research experience at top labs)
  • Published research in RL, multi-agent systems, or LLM training
  • Strong Python and PyTorch/JAX skills—comfortable implementing novel research ideas
  • Genuine passion for games and what they teach about intelligence
  • Comfortable at early-stage startup (we're 2 years funded, moving fast)

Preferred:

  • Experience at DeepMind, FAIR, OpenAI, Anthropic, or top academic groups
  • Background in game-playing AI (AlphaGo lineage, Cicero, game engines)
  • Experience with pre-training or post-training at scale (260B+ parameter models)
  • Familiarity with RLHF, reward modeling, or alignment research
What We Offer
  • Location: Toronto or New York preferred; flexible for exceptional remote candidates
  • Partnerships: Direct collaboration with research groups at six universities
  • Traction: Live contracts, accepted papers, millions of players in games using our agents
  • Runway: $3.6M raised, two years funded

Good Start Labs is committed to building a diverse team. We encourage applications from people underrepresented in AI research. We provide visa sponsorship for exceptional candidates.

Life's better with play.

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