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Senior Machine Learning Ops Engineer Jobs in Mundelein, IL

... engineers * An environment that values deep work, clear thinking, and real impact * Regular team events and offsites * Equipment and learning budget to help you do your best work and keep up with the ...

Senior Machine Learning Engineer (LLMs)

Chicago, IL · On-site

$126K - $166K/yr

... engineers * An environment that values deep work, clear thinking, and real impact * Regular team events and off‑sites * Equipment and learning budget to help you do your best work and keep up with ...

Senior Machine Learning Engineer (LLMs)

Chicago, IL · On-site

$126K - $166K/yr

... engineers * An environment that values deep work, clear thinking, and real impact * Regular team events and off-sites * Equipment and learning budget to help you do your best work and keep up with ...

Senior ML Engineer

Chicago, IL · Remote

$180K - $240K/yr

Career Renew is recruiting for one of its clients a Senior Machine Learning Engineer - this is a fully remote role for US/Canada based candidates. Salary range: 180-240K USD plus benefits plus equity.

Machine Learning Engineer Position Overview Paylocity is growing its Machine Learning Engineering organization! Our machine learning engineering team is responsible for developing infrastructure and ...

Machine Learning Engineer

Chicago, IL · On-site

$80 - $120/hr

Preferred Qualifications PhD in Mathematics, Engineering, Physics or related field; 4-8 years experience working in Machine Learning; Experience with deep learning frameworks like TensorFlow or ...

Senior AI Machine Learning Engineer

Chicago, IL · On-site

$126K - $166K/yr

Sr Data Engineer - GE07BE We're determined to make a difference and are proud to be an insurance ... The Hartfordis seeking aSenior AI Machine Learning Engineerwithin Employee Benefits Applied AI and ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Lead Machine Learning Engineer

Chicago, IL · On-site

$105K - $139K/yr

Lead Machine Learning Engineers at Thoughtworks use modern architectures to develop end-to-end scalable machine learning systems and applications. They use their specialized depth and breadth of ...

Showing results 21-40

Senior Machine Learning Ops Engineer information

See Mundelein, IL salary details

$60.7K

$129.2K

$187.3K

How much do senior machine learning ops engineer jobs pay per year?

As of Aug 11, 2026, the average yearly pay for senior machine learning ops engineer in Mundelein, IL is $129,203.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,700.00 and $146,500.00 per year, depending on experience, location, and employer.

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

To thrive as a Senior Machine Learning Ops Engineer, you need expertise in machine learning, software engineering, cloud platforms, and experience with CI/CD pipelines, often supported by a computer science degree or equivalent experience. Proficiency with tools like Docker, Kubernetes, TensorFlow, PyTorch, and cloud services such as AWS, GCP, or Azure is typically required, along with familiarity with MLOps frameworks. Strong problem-solving, collaboration, and communication skills help you work effectively with cross-functional teams and manage complex ML model deployments. These skills are essential to ensure reliable, scalable, and efficient deployment of machine learning models in production environments.

What are some common challenges faced by senior machine learning ops engineers when deploying models to production?

Senior Machine Learning Ops Engineers often encounter challenges such as ensuring model reproducibility, managing model versioning, and automating deployment pipelines for scalability. Another key challenge is monitoring model performance and data drift in production, which requires robust logging and alerting systems. Collaborating closely with data scientists, software engineers, and IT teams is essential to address these challenges and maintain a stable, efficient ML infrastructure.

What is the difference between Senior Machine Learning Ops Engineer vs Data Engineer?

AspectSenior Machine Learning Ops EngineerData Engineer
CredentialsExperience with ML frameworks, cloud platforms, scripting, and DevOps toolsStrong SQL, ETL, database, and programming skills, often with cloud experience
Work EnvironmentFocus on deploying, monitoring, and maintaining ML models in productionDesigning and building data pipelines and infrastructure for data processing
Industry UsageCommon in AI/ML-focused companies, tech firms, and data-driven organizationsWidespread across industries for data management and analytics

While both roles involve working with data and cloud platforms, the Senior Machine Learning Ops Engineer specializes in deploying and maintaining machine learning models, whereas the Data Engineer focuses on building data pipelines and infrastructure. Understanding these distinctions helps in choosing the right career path or job search focus.

What is a senior machine learning ops engineer?

Senior Machine Learning Ops (MLOps) Engineers are experienced professionals who design, build, and maintain the infrastructure and tools needed to deploy, monitor, and scale machine learning models in production environments. They work at the intersection of data science, software engineering, and DevOps to ensure ML models are robust, reliable, and secure. Their responsibilities often include automating model training pipelines, managing cloud resources, implementing CI/CD for ML, and ensuring model reproducibility. Senior MLOps Engineers also mentor junior staff and help define best practices for the organization’s ML workflow.
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Senior Machine Learning Engineer (LLMs)

Albi

Chicago, IL

$126K - $166K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 5 days ago


Job description

We're building deeply integrated LLMs into a real product used daily by restoration companies running thousands of jobs. This is not a "prompt engineer" role. You'll design, train, and ship domain-specific language models that automate real workflows and move real revenue.

You will:

  • Own endtoend LLM systems: architecture, training, evals, and iteration
  • Finetune and extend existing models (LoRA, instruction tuning, RLHF)
  • Build and maintain data pipelines from product databases, documents, APIs, and logs
  • Ship reliable, monitored, production models with clear guardrails
  • Collaborate closely with product and engineering to turn messy realworld problems into working systems
  • Build and coordinate the AI engineering team
  • Use Claude Code as a core tool for development, refactors, tests, and experiments

This is for you if:

  • "How does this actually work under the hood?" is your default question
  • You're fine sitting with a hard problem for days and reading papers on weekends to figure it out
  • If there's something interesting to learn or solve, it doesn't matter if it's Saturday or 1 a.m., you're in
  • You build side projects nobody asked for and write cleaner code than anyone requires
  • You're quietly competitive, selftaught in at least one major skill, and think in systems
  • You're slightly allergic to meetings without a clear purpose or owner

Requirements

  • 5+ years of real world experience in ML / AI engineering
  • Proven experience training or substantially contributing to training LLMs (not just calling APIs)
  • Deep understanding of transformers, attention, and training dynamics
  • Strong Python plus PyTorch or JAX
  • Experience with largescale data pipelines and experiment tracking
  • Handson finetuning (LoRA, instruction / SFT, RLHF or similar)
  • Comfortable using Claude Code as part of your daily workflow
  • Able to explain complex systems simply to nontechnical stakeholders and go deep with experts
  • Track record of owning projects endtoend and mentoring other engineers

Nice to have:

  • Distributed training (FSDP, DeepSpeed, Megatron, etc.)
  • Inference optimization (quantization, speculative decoding, vLLM, Triton)
  • Experience shipping LLM features in production SaaS
  • Opensource contributions or published work or patents in ML / NLP
  • Microsoft Foundry experience

Benefits

  • Competitive salary (based on experience and location)
  • Generous PTO
  • Medical, dental, and vision coverage
  • 401(k) plan
  • High ownership and autonomy over your work
  • Direct collaboration with a small team of smart, kind, motivated engineers
  • An environment that values deep work, clear thinking, and real impact
  • Regular team events and offsites
  • Equipment and learning budget to help you do your best work and keep up with the frontier