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Ai Engineer Llm Jobs (NOW HIRING)

Entertainment Partners

AI Engineer

Tempe, AZ

This role sits at the intersection of applied ML engineering, LLM product development, and production-grade system design. The AI Senior Software Engineer is responsible for building, training ...

Entertainment Partners

AI Engineer

Tempe, AZ · On-site

This role sits at the intersection of applied ML engineering, LLM product development, and production-grade system design. The AI Senior Software Engineer is responsible for building, training ...

Cantor Fitzgerald Securities

AI Engineer

Manhattan, NY · On-site

$300K - $350K/yr

Your expertise will be instrumental in developing agentic AI workflows, evaluating LLM-powered systems, and contributing to our technical strategy and architectural decisions. As an AI Engineer, you ...

Bomnin Chevrolet Dadeland

Sr. AI/ML Engineer (LLM)

Miami, FL · On-site

$99K - $137K/yr

Provide AI/ML technical leadership and mentorship to other engineers on the team. * Ensure that LLM integrations are efficient, scalable, and secure, adhering to industry best practices. Position ...

Cantor Fitzgerald Securities

AI Engineer

Manhattan, NY

$300K - $350K/yr

Your expertise will be instrumental in developing agentic AI workflows, evaluating LLM-powered systems, and contributing to our technical strategy and architectural decisions. As an AI Engineer, you ...

Corning

This role is part of our Digital & IT organization and is focused on applying AI through hands-on software engineering, Python development, APIs, LLM-enabled solutions, workflow automation, and ...

Corning

This role is part of our Digital & IT organization and is focused on applying AI through hands-on software engineering, Python development, APIs, LLM-enabled solutions, workflow automation, and ...

Corning

This role is part of our Digital & IT organization and is focused on applying AI through hands-on software engineering, Python development, APIs, LLM-enabled solutions, workflow automation, and ...

David Joseph & Company

AI Engineer

San Francisco, CA · Remote

$150K - $250K/yr

San Francisco, CA (HQ); remote within the US The Role We're looking for an AI Engineer to build and ship LLM-powered healthcare applications, with ownership over new AI workflows from prototype to ...

Allstate

Senior AI Engineer

Chicago, IL

$126K - $166K/yr

Engineer LLM ‑ powered services for schema understanding, semantic alignment, ontology enrichment ... Experience building AI ‑ assisted analytics or semantic layers for BI or NLQ use cases. The ...

Themesoft, Inc.

AI Engineer

Charlotte, NC · On-site

Hands on AI experience developing LLM based applications * Orchestration using Langraph/Google ADK * MCP experience About this role: * Client is seeking a Lead AI Engineer with deep expertise in ...

Tror AI for everyone

AI Engineer

Lake Mary, FL · On-site

AI Engineer Job Location: Lake Mary, FL (3 Days Onsite) Job Type: Contract Need 11+ Years of ... LLM Fundamentals * Prompt Engineering * Tokenization, context windows * Model selection * Handling ...

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As of Jul 21, 2026, the average hourly pay for ai engineer llm in the United States is $53.63, according to ZipRecruiter salary data. Most workers in this role earn between $43.27 and $62.26 per hour, depending on experience, location, and employer.
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Infographic showing various Ai Engineer Llm job openings in the United States as of July 2026, with employment types broken down into 75% Full Time, 22% Part Time, and 3% Contract. Highlights an 66% Physical, 3% Hybrid, and 31% Remote job distribution, with an average salary of $111,552 per year, or $53.6 per hour.
AI/ML Research Engineer, LLM Post-Training & Evaluation

AI/ML Research Engineer, LLM Post-Training & Evaluation

Innodata Inc.

Remote

Full-time

Posted 14 days ago

Innodata rating

7.3

Company rating: 7.3 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

150th of 209 rated software companies

Job description

Innodata (Nasdaq: INOD) is a global data engineering company. We believe that data and Artificial Intelligence (AI) are inextricably linked. Our mission is to enable the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and human expertise required to build AI systems that can be trusted at scale. We provide a range of transferable solutions, platforms, and services for Generative AI / AI builders and adopters. In every relationship, we honor our 36+ year legacy delivering the highest quality data and outstanding outcomes for our customers.
Scope of the Role:
Innodata is expanding its team of technical experts in LLM training, post-training, and evaluation systems. As an AI/ML Research Engineer, LLM Training & Evaluation, you will build and optimize the technical foundations that power model improvement for foundation model builders and leading labs.
This role is ideal for someone who has hands-on experience fine-tuning and evaluating large language models (and ideally multimodal models), and who can bridge research and engineering in real-world customer environments. You will work closely with Language Data Scientists, Applied Research Scientists, data engineers, and client technical stakeholders to design and implement robust training/evaluation pipelines using both human-in-the-loop and AI-augmented methods.
The ideal candidate brings a strong computer science / machine learning engineering background, experience with modern LLM post-training workflows, and the ability to engage credibly with technical counterparts at leading AI organizations.
What You'll Own:
As an AI/ML Research Engineer, LLM Training & Evaluation, you will design and implement the pipelines and tooling that connect data, evaluation, and post-training. You will help customers and internal teams move from evaluation findings to measurable model improvements.
Your work may include building fine-tuning workflows (e.g., supervised fine-tuning and preference-based optimization), integrating evaluation harnesses into model development loops, improving experiment reliability and throughput, and supporting advanced evaluation scenarios such as long-context, cross-modal, and dynamic multi-turn interactions.
You will also contribute to Innodata's internal R&D efforts, including benchmark datasets, evaluation frameworks, and reusable infrastructure for model assessment and post-training experimentation. Additional responsibilities include (but are not limited to):
  • Lead or co-lead technically complex ML engineering projects from initial customer discussions through implementation and delivery
  • Design, build, and improve LLM training and post-training pipelines, including data ingestion, preprocessing, fine-tuning, evaluation, and experiment tracking
  • Implement and optimize evaluation systems for LLMs and multimodal models, including offline benchmarks and task-specific test harnesses
  • Integrate human-in-the-loop and AI-augmented evaluation signals into model development workflows
  • Build robust infrastructure and tooling for reproducible experimentation, metrics logging, and regression monitoring
  • Diagnose model behavior and pipeline failures, including data issues, training instability, metric inconsistencies, and evaluation drift
  • Collaborate with Language Data Scientists and Applied Research Scientists to translate evaluation frameworks into executable systems
  • Work closely with customer technical stakeholders to understand goals, constraints, and success criteria; propose and implement technically sound solutions
  • Contribute to internal research and platform development, including benchmark frameworks, evaluation tooling, and post-training workflow improvements
  • Contribute to best practices and standards for LLM training, evaluation, and quality assurance across projects
  • Mentor junior engineers and contribute to technical design reviews, documentation, and engineering rigor across the team

You'll Thrive in This Role If You Have:
  • BS/MS/PhD in Computer Science, Machine Learning, AI, Applied Mathematics, or a related quantitative technical field (MS/PhD preferred)
  • 2-3 years of relevant industry or research engineering experience in ML/AI systems
  • Hands-on experience with LLM training / fine-tuning / post-training, including at least one of:
    • supervised fine-tuning (SFT)
    • preference optimization (e.g., DPO or related methods)
    • RLHF / RLAIF-style workflows
    • task- or domain-adaptation of foundation models
  • Strong programming skills in Python and experience building production-quality ML code
  • Experience with modern ML frameworks (e.g., PyTorch, JAX, TensorFlow) and model libraries/tooling (e.g., Hugging Face ecosystem, vLLM, distributed training stacks)
  • Experience designing and implementing evaluation pipelines for LLM/ML systems, including metrics computation, dataset handling, and experiment comparisons
  • Strong understanding of data pipelines and ML systems engineering, including reproducibility, observability, and debugging
  • Experience with large-scale distributed ML systems and performance optimization for training/evaluation workloads (GPU/accelerator environments preferred)
  • Experience with large-scale data processing and workflow orchestration in support of model training/evaluation
  • Ability to collaborate directly with technical stakeholders including research scientists, ML engineers, data engineers, and customer technical leads
  • Strong written and verbal communication skills, including the ability to explain complex technical tradeoffs to both technical and non-technical audiences

Technical Skills
ML / LLM Engineering
  • Experience training, fine-tuning, and evaluating transformer-based models
  • Understanding of post-training workflows and model iteration loops
  • Familiarity with inference-time considerations (latency, throughput, memory/performance tradeoffs) where relevant to evaluation or deployment

Evaluation & Experimentation
  • Experience implementing automated evaluation pipelines and test harnesses
  • Experience with experiment tracking, versioning, and reproducibility practices
  • Ability to assess metric quality and ensure consistency across model comparisons

Software / Data Engineering
  • Proficiency in Python and strong software engineering fundamentals
  • Experience with data processing pipelines, storage formats, and scalable dataset workflows
  • Familiarity with CI/CD, testing, and engineering quality practices for ML systems

The expected salary range for this position is $80,000 - $175,000 USD per year, based on experience, skills, and qualifications.
Please be aware of recruitment scams involving individuals or organizations falsely claiming to represent employers. Innodata will never ask for payment, banking details, or sensitive personal information during the application process. To learn more on how to recognize job scams, please visit the Federal Trade Commission's guide at https://consumer.ftc.gov/articles/job-scams.
If you believe you've been targeted by a recruitment scam, please report it to Innodata at verifyjoboffer@innodata.com and consider reporting it to the FTC at ReportFraud.ftc.gov.

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