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Senior Machine Learning Engineer Jobs in Missouri

Jobgether

Our partner is looking for a Machine Learning Engineer - Distillation based in Netherlands. This ... Collaboration with a small, senior team combining research expertise and engineering excellence.

Jobgether

$88K - $106K/yr

Our partner is looking for a Machine Learning Engineer - Inference Optimization based in Netherlands. This role offers the opportunity to optimize the performance of advanced machine learning systems ...

Jobgether

Our partner is looking for a Machine Learning Engineer - Training Optimization based in Netherlands. This role offers the opportunity to improve the foundations behind large-scale AI model ...

Bespoke Labs

Machine Learning Engineer

Saint Louis, MO · On-site

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 ...

Bespoke Labs

Machine Learning Engineer

Columbia, MO · On-site

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 ...

Bespoke Labs

Machine Learning Engineer

Springfield, MO · On-site

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 ...

Instacart

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...

Instacart

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...

Instacart

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...

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All JobsMachine Learning Engineer JobsSenior Machine Learning Engineer JobsSenior Machine Learning Engineer Jobs in Missouri

Senior Machine Learning Engineer information

See Missouri salary details

$55.8K

$118.7K

$172.1K

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

As of Jul 28, 2026, the average yearly pay for senior machine learning engineer in Missouri is $118,711.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,000.00 and $134,600.00 per year, depending on experience, location, and employer.

What are some common challenges Senior Machine Learning Engineers face when deploying models to production, and how can they be addressed?

Senior Machine Learning Engineers often encounter challenges related to model scalability, maintaining performance in real-world scenarios, and ensuring reliable integration with existing systems. Addressing these challenges typically involves thorough testing, implementing robust monitoring for model drift, and collaborating closely with DevOps and software engineering teams to streamline deployment pipelines. Staying updated on best practices in MLOps and adopting tools for automated deployment and monitoring can greatly improve the reliability and efficiency of production models.

What does a Senior Machine Learning Engineer do?

A Senior Machine Learning Engineer designs, develops, and implements machine learning models to solve complex problems. They are responsible for selecting appropriate algorithms, preprocessing data, and optimizing model performance. Additionally, they collaborate with data scientists, software engineers, and product teams to integrate machine learning solutions into production systems. Senior engineers also mentor junior team members and contribute to setting technical direction for machine learning projects.

What are the key skills and qualifications needed to thrive as a Senior Machine Learning Engineer, and why are they important?

To thrive as a Senior Machine Learning Engineer, you need advanced knowledge of machine learning algorithms, statistical modeling, and programming languages like Python or Java, typically supported by a degree in computer science or a related field. Experience with frameworks and tools such as TensorFlow, PyTorch, scikit-learn, and cloud platforms, as well as familiarity with version control and CI/CD systems, is essential. Strong problem-solving, communication, and leadership skills help you collaborate effectively and mentor junior team members. These capabilities are crucial for designing scalable ML solutions and driving impactful results within complex, dynamic projects.

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

AspectSenior Machine Learning EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience with ML frameworksBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops and deploys ML models in production systemsAnalyzes data, builds models, and provides insights
Industry UsageTech, finance, healthcare, e-commerceResearch, finance, marketing, tech

While both roles require strong technical skills and knowledge of machine learning, Senior Machine Learning Engineers focus more on deploying scalable ML solutions in production environments, whereas Data Scientists primarily analyze data and develop models for insights. The roles often overlap but differ in their core responsibilities and focus areas.

What are the most commonly searched types of Machine Learning Engineer jobs in Missouri? The most popular types of Machine Learning Engineer jobs in Missouri are:
What are popular job titles related to Senior Machine Learning Engineer jobs in Missouri? For Senior Machine Learning Engineer jobs in Missouri, the most frequently searched job titles are:
What job categories do people searching Senior Machine Learning Engineer jobs in Missouri look for? The top searched job categories for Senior Machine Learning Engineer jobs in Missouri are:
What cities in Missouri are hiring for Senior Machine Learning Engineer jobs? Cities in Missouri with the most Senior Machine Learning Engineer job openings:
Senior Machine Learning Engineer jobs near you
Infographic showing various Senior Machine Learning Engineer job openings in Missouri as of July 2026, with employment types broken down into 93% Full Time, 5% Part Time, and 2% Contract. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution, with an average salary of $118,711 per year, or $57.1 per hour.

Machine Learning Engineer - Distillation

Jobgether

On-site, Remote

Full-time

Posted 4 days ago

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Machine Learning Engineer - Distillation based in Netherlands.

This role offers the opportunity to advance the efficiency and scalability of next-generation machine learning systems.
You will work at the intersection of research and production, transforming cutting-edge model optimization techniques into real-world solutions.
The position focuses on building smaller, faster, and more cost-effective AI models while maintaining high-quality performance.
You will design advanced distillation pipelines, run large-scale experiments, and contribute directly to production systems.
This is an opportunity for an ML engineer who enjoys deep technical challenges, experimentation, and practical innovation.
You will join a collaborative environment where your work directly influences model quality, performance, and product impact.

Accountabilities

As a Machine Learning Engineer focused on Distillation, you will design, develop, and optimize machine learning systems that improve model efficiency without compromising performance. You will combine research expertise with engineering execution to build scalable AI solutions.

  • Design and implement advanced knowledge distillation pipelines, including teacher-student approaches, self-distillation, and multi-teacher architectures.
  • Distill large foundation models into smaller, faster, and more efficient models optimized for production inference.
  • Run large-scale machine learning experiments to evaluate model quality, latency, efficiency, and cost tradeoffs.
  • Analyze experimental results and use insights to improve model performance and optimization strategies.
  • Collaborate with research teams to transform emerging distillation techniques into reliable production-ready implementations.
  • Optimize training and inference performance, including memory usage, throughput, latency, and computational efficiency.
  • Develop and improve internal tools, evaluation frameworks, and experiment tracking systems.
  • Contribute to improving machine learning workflows and engineering best practices.
  • Explore opportunities to contribute to open-source models, research initiatives, or technical tooling.
Requirements

The ideal candidate is a machine learning engineer with strong experience in deep learning, model optimization, and production-oriented AI development. You should have hands-on experience with distillation techniques and the ability to balance research innovation with practical engineering delivery.

  • Strong background in machine learning, deep learning, and neural network architectures.
  • Hands-on experience implementing model distillation techniques for large language models or other neural networks.
  • Solid understanding of training dynamics, optimization methods, loss functions, and model evaluation.
  • Experience working with PyTorch, JAX, or similar modern machine learning frameworks.
  • Experience running experiments in multi-GPU or distributed training environments.
  • Ability to evaluate and optimize tradeoffs between model quality, performance, latency, and cost.
  • Strong programming and software engineering skills with the ability to build production-ready ML systems.
  • Practical mindset focused on shipping impactful solutions rather than only theoretical research.
  • Experience with inference optimization techniques such as quantization, pruning, or kernel optimization is a plus.
  • Familiarity with language model evaluation methodologies is preferred.
  • Open-source contributions, research publications, or experience in fast-moving startup environments are considered valuable.
Benefits
  • Competitive compensation package with meaningful equity opportunities.
  • Opportunity to work on core machine learning systems that directly impact product performance and efficiency.
  • High ownership role with significant influence over technical direction and roadmap.
  • Collaboration with a small, senior team combining research expertise and engineering excellence.
  • Remote-friendly work environment with an async-first culture.
  • Opportunity to solve challenging AI optimization problems at scale.
  • Ability to contribute to advanced model development and emerging AI technologies.
  • Fast-paced environment that encourages innovation, experimentation, and technical growth.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
 Why Apply Through Jobgether? 
 
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
 
 
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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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