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Machine Learning Jobs in Missouri (NOW HIRING)

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 ...

Walmart

Staff, Machine Learning Engineer

Noel, MO · On-site

$130K - $260K/yr

We are looking for a strong Staff Machine Learning Engineer who has the passion to develop AI driven intelligent products for the Associate Productivity and Experience team, with the ability to ...

Walmart

Staff, Machine Learning Engineer

Cassville, MO · On-site

$130K - $260K/yr

We are looking for a strong Staff Machine Learning Engineer who has the passion to develop AI driven intelligent products for the Associate Productivity and Experience team, with the ability to ...

Walmart

Staff, Machine Learning Engineer

Anderson, MO · On-site

$130K - $260K/yr

We are looking for a strong Staff Machine Learning Engineer who has the passion to develop AI driven intelligent products for the Associate Productivity and Experience team, with the ability to ...

Quora

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code editing, RAG, etc. Our team of Machine Learning Engineers have high impact by advancing the current ...

Quora

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code editing, RAG, etc. Our team of Machine Learning Engineers have high impact by advancing the current ...

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All JobsMachine Learning JobsMachine Learning Jobs in Missouri

Machine Learning information

See Missouri salary details

$23.9K

$39.9K

$82.5K

How much do machine learning jobs pay per year?

As of Aug 6, 2026, the average yearly pay for machine learning in Missouri is $39,944.00, according to ZipRecruiter salary data. Most workers in this role earn between $30,500.00 and $43,100.00 per year, depending on experience, location, and employer.

What is a machine learning?

A Machine Learning job involves developing algorithms and models that enable computers to learn from data and make predictions or decisions without explicit programming. Professionals in this field work with large datasets, design and train machine learning models, and optimize them for performance and accuracy. Roles often require knowledge of programming languages like Python or R, experience with frameworks like TensorFlow or PyTorch, and an understanding of statistics and data science principles. Machine learning engineers and data scientists collaborate with software developers and domain experts to build AI-driven solutions for various industries.

What are the typical day-to-day responsibilities in a machine learning role?

As a machine learning professional, your daily tasks may include data preprocessing, developing and training models, evaluating performance metrics, and experimenting with algorithms to optimize results. You’ll often collaborate closely with data scientists, software engineers, and business stakeholders to align technical solutions with organizational goals. Regular activities can also involve deploying models to production, monitoring performance, and troubleshooting any issues that arise post-deployment. Staying up to date with recent ML research and participating in team discussions or code reviews are also common parts of the job.

What jobs can I get with machine learning?

With a background in machine learning, you can pursue roles such as machine learning engineer, data scientist, AI researcher, or data analyst. These positions typically require skills in programming languages like Python or R, knowledge of algorithms, and experience with tools like TensorFlow or PyTorch.

What are the key skills and qualifications needed to thrive in a machine learning position?

To thrive in Machine Learning, you need a solid background in mathematics, statistics, programming (especially Python or R), and a formal degree in computer science, data science, or a related field. Experience with popular ML frameworks (such as TensorFlow, PyTorch, or Scikit-learn), version control, and relevant certifications like AWS Certified Machine Learning are highly valued. Strong problem-solving skills, curiosity, clear communication, and the ability to work both independently and within multidisciplinary teams make candidates stand out. These skills and qualities are essential for developing robust models, staying updated with technology advancements, and collaborating effectively on complex projects.

What are the most commonly searched types of Machine Learning jobs in Missouri? The most popular types of Machine Learning jobs in Missouri are:
What are popular job titles related to Machine Learning jobs in Missouri? For Machine Learning jobs in Missouri, the most frequently searched job titles are:
What job categories do people searching Machine Learning jobs in Missouri look for? The top searched job categories for Machine Learning jobs in Missouri are:
What cities in Missouri are hiring for Machine Learning jobs? Cities in Missouri with the most Machine Learning job openings:
Machine Learning jobs near you
Infographic showing various Machine Learning job openings in Missouri as of August 2026, with employment types broken down into 50% Full Time, and 50% Part Time. Highlights an 100% In-person job distribution, with an average salary of $39,944 per year, or $19.2 per hour.

Machine Learning Engineer - Inference Optimization

Jobgether

On-site, Remote

$88K - $106K/yr

Full-time

Posted 14 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 - Inference Optimization based in Netherlands.

This role offers the opportunity to optimize the performance of advanced machine learning systems used in real-world production environments.
You will work at the intersection of research and engineering, transforming cutting-edge models into fast, reliable, and cost-efficient solutions.
Your work will directly impact model scalability, user experience, and the efficiency of AI-powered products.
You will dive deep into performance optimization, from model architecture and GPU execution to large-scale inference infrastructure.
Working with talented research, infrastructure, and product teams, you will help push the boundaries of what AI systems can achieve.
This position is ideal for an engineer who enjoys solving complex technical challenges and building high-performance ML systems from the ground up.

Accountabilities

As a Machine Learning Engineer specializing in inference optimization, you will own the performance and scalability of machine learning models in production. You will combine deep ML expertise, systems engineering, and performance analysis to deliver faster, more efficient AI experiences.

  • Optimize machine learning inference systems to improve latency, throughput, scalability, and operational cost.
  • Profile and identify bottlenecks across GPU and CPU inference pipelines, including memory usage, kernels, batching strategies, and data flow.
  • Implement advanced optimization techniques such as quantization, KV-cache optimization, speculative decoding, batching, streaming, and model simplification.
  • Collaborate with research engineers to productionize new model architectures and translate experimental results into reliable systems.
  • Build, improve, and maintain inference-serving infrastructure using modern frameworks, custom runtimes, or specialized serving solutions.
  • Benchmark model performance across different hardware environments, including GPUs, CPUs, and cloud-based systems.
  • Improve system reliability, monitoring, observability, and cost efficiency under real production workloads.
  • Contribute to engineering practices that improve the quality, scalability, and maintainability of ML infrastructure.
Requirements:

The ideal candidate is a technically strong machine learning engineer with experience optimizing production inference systems and a passion for high-performance AI engineering. You should enjoy working on complex technical problems, experimenting with new approaches, and taking ownership of critical systems.

  • Strong professional experience in ML inference optimization, high-performance machine learning systems, or related areas.
  • Deep understanding of machine learning fundamentals, including neural network architectures, attention mechanisms, memory optimization, and compute graphs.
  • Hands-on experience with PyTorch or similar deep learning frameworks and deploying models into production environments.
  • Experience with GPU performance optimization, including technologies such as CUDA, ROCm, Triton, or kernel-level tuning.
  • Proven experience scaling inference systems for real users beyond research prototypes or benchmarks.
  • Strong programming skills and the ability to work across machine learning and systems engineering domains.
  • Ability to operate effectively in fast-paced environments with ownership, autonomy, and evolving priorities.
  • Experience with inference frameworks such as TensorRT, ONNX Runtime, vLLM, or Triton is a plus.
  • Familiarity with large language models, long-context inference, distributed systems, low-latency services, or hardware optimization is considered an advantage.
  • Contributions to open-source ML systems or inference tooling are a plus.
Benefits:
  • Competitive compensation package with meaningful equity participation.
  • Opportunity to work on performance-critical AI systems with direct product impact.
  • High level of ownership over infrastructure that shapes scalability and efficiency.
  • Close collaboration with research, infrastructure, and product teams.
  • Opportunity to work on advanced machine learning technologies and real-world AI applications.
  • Engineering-focused culture that values technical excellence, experimentation, and quality.
  • Flexible remote work environment.
  • Opportunity to contribute to the growth of an innovative AI-focused organization.
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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