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Remote Machine Learning Postdoc Jobs in Missouri

Jobgether

As a Machine Learning Product Manager, you will lead the strategy, development, and optimization of ... Fully remote work environment with flexibility to work from anywhere within eligible European ...

Jobgether

$40.75 - $55.75/hr

This is an excellent opportunity for an experienced DevOps professional to help build and optimize enterprise-scale machine learning infrastructure in a fully remote environment. In this role, you ...

New

Kohl's

$89K - $122K/yr

Design, build, and maintain scalable machine learning infrastructure, including model serving (real-time and batch), training environments, and orchestration systems, with a focus on performance ...

Jobgether

$79K - $104K/yr

Working in a fully remote, international environment, you will help establish best practices and drive innovation across the entire machine learning lifecycle, enabling the delivery of reliable and ...

Koantek

Senior AI Engineer

Chesterfield, MO · Remote

$54.75 - $70.50/hr

This remote role requires a blend of advanced Machine Learning (ML) expertise, deep knowledge of MLOps principles, and a proven track record in client-facing implementation. The successful candidate ...

Third-Party Job Posts

Location - Remote (Europe) How You'll Make an Impact: As a Staff Machine Learning Engineer , you will play a key role in building and implementing features that empower lodging customers to make data ...

Jobgether

In this role, you will combine expertise in machine learning, generative AI, and scientific data ... Fully remote position with collaboration across the European CET time zone. * Immediate opportunity ...

New

Jobgether

The work operates at the intersection of machine learning, distributed systems, and advertising ... Remote-first international work environment with high autonomy and flexibility. * Exposure to ...

Stellar IT Solutions LLC

Data Scientist

Saint Louis, MO · Remote

$55 - $60/hr

Data Scientist Remote 12 Month Contract to hire Data Scientist - Profile Overview This is a data ... Solid traditional Machine Learning: Feature engineering, model training, evaluation * Not a model ...

Jobgether

$80K - $110K/yr

Adapt machine learning models and vision pipelines to support new sports, leagues, stadiums, camera ... Fully remote position for professionals residing in Europe. * Flexible working hours with a strong ...

Kohl's

Conceptual understanding of Data Mining and Machine Learning methodologies for analytical application Preferred * Degree in Mathematics or Statistics, Economics, Computer Science, Predictive ...

micro1 AI

Engineering AI Evaluator (PhD)

Kansas City, MO · Remote

$80 - $90/hr

Remote micro1 is engaging PhD-level Engineers in Electrical, Mechanical, or Chemical disciplines to ... Experience with or interest in AI, machine learning, or technology-driven projects (a plus, not ...

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All JobsMachine Learning Postdoc JobsRemote Machine Learning Postdoc JobsRemote Machine Learning Postdoc Jobs in Missouri

Remote Machine Learning Postdoc information

Is ML a high paying job?

Machine learning postdoctoral positions are generally well-paid compared to many academic roles, with salaries often ranging from $60,000 to over $100,000 annually depending on experience, location, and funding. These roles typically require strong programming skills in Python or R and knowledge of algorithms and data analysis, which can contribute to higher compensation levels.

Is a PhD in ML worth it?

A PhD in machine learning can enhance qualifications for a remote machine learning postdoc position, often leading to higher-level research opportunities and increased earning potential. However, it requires significant time investment and may not be necessary for industry roles that value practical skills and experience with tools like Python and TensorFlow. The decision depends on career goals and the specific requirements of the desired position.

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

A Remote Machine Learning Postdoc requires a PhD in computer science, statistics, or a related field, with expertise in machine learning algorithms, statistical modeling, and research methodologies. Proficiency in programming languages like Python or R, experience with machine learning frameworks such as TensorFlow or PyTorch, and familiarity with version control systems (e.g., Git) are typically necessary. Strong written and verbal communication, self-motivation, and collaboration skills are vital for remote research and effective teamwork. These capabilities enable impactful independent research, smooth collaboration across distributed teams, and the successful dissemination of findings to the wider scientific community.

Is a postdoc harder than a PhD?

A remote machine learning postdoc typically involves more specialized research, higher expectations for independence, and often requires advanced skills in programming and data analysis. While a PhD focuses on completing a dissertation and gaining foundational expertise, a postdoc emphasizes producing publishable research and may involve longer hours and greater responsibility, making it generally more demanding in terms of research output and expertise. However, the difficulty varies based on individual experience and research environment.

What is a Remote Machine Learning Postdoc?

A Remote Machine Learning Postdoc is a postdoctoral researcher specializing in machine learning who works predominantly or entirely from a location outside their host institution, often from home. Their work involves conducting advanced research, developing new algorithms, analyzing data, and publishing findings related to machine learning while collaborating virtually with faculty and research teams. This role is ideal for researchers seeking flexibility or those who cannot relocate but wish to contribute to academic or industrial research from a distance.

Do you need H-1B for postdoc?

A remote machine learning postdoctoral position typically does not require H-1B sponsorship if the candidate is already authorized to work in the country, such as through a visa or citizenship. However, international candidates may need H-1B or other work visas depending on the employer and local immigration laws. Employers often sponsor visas for postdocs to comply with legal requirements and facilitate employment.

What are some common challenges faced by remote machine learning postdocs when collaborating with research teams?

Remote machine learning postdocs often encounter challenges related to communication and coordination, especially when working across different time zones or with teams that have varying schedules. Effective collaboration usually requires proactive communication through virtual meetings, shared code repositories, and regular progress updates. Building rapport with colleagues and staying engaged with ongoing research discussions can take extra effort remotely, but leveraging collaborative tools and participating in virtual seminars or group chats can help bridge the gap. Being organized and self-motivated is key to ensuring productive contributions to the team’s research objectives.
What are popular job titles related to Remote Machine Learning Postdoc jobs in Missouri? For Remote Machine Learning Postdoc jobs in Missouri, the most frequently searched job titles are:
What job categories do people searching Remote Machine Learning Postdoc jobs in Missouri look for? The top searched job categories for Remote Machine Learning Postdoc jobs in Missouri are:
What cities in Missouri are hiring for Remote Machine Learning Postdoc jobs? Cities in Missouri with the most Remote Machine Learning Postdoc job openings:
Remote Machine Learning Postdoc jobs near you

Machine Learning Product Manager

Jobgether

On-site, Remote

Full-time

This job post has expired 1 day ago. Applications are no longer accepted.

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 Product Manager based in Netherlands.

As a Machine Learning Product Manager, you will lead the strategy, development, and optimization of intelligent decision-making systems that drive meaningful business outcomes. Working at the intersection of product, data science, engineering, analytics, and commercial teams, you will transform complex challenges into scalable AI-powered solutions. This role combines strategic thinking with technical product leadership, requiring a strong understanding of machine learning, experimentation, and data-driven decision-making. You will shape how automated systems support growth, improve operational efficiency, and balance human oversight with intelligent automation. Ideal for a product leader who enjoys navigating ambiguity and solving high-impact problems, this position offers the opportunity to influence core business performance through innovative technology and cross-functional collaboration.

Accountabilities
  • Define and own the product vision, strategy, and roadmap for machine learning-powered decisioning and optimization capabilities.
  • Translate business objectives into clear product requirements, user stories, decision frameworks, and measurable success metrics.
  • Collaborate closely with Data Science, Engineering, Analytics, Commercial, and Leadership teams to develop intelligent systems that support growth and operational efficiency.
  • Identify, evaluate, and prioritize high-impact use cases for machine learning and automated decision-making across the business.
  • Lead discovery initiatives to understand existing workflows, operational challenges, and opportunities for optimization through AI-driven solutions.
  • Partner with technical teams to define data requirements, model objectives, experimentation frameworks, monitoring strategies, and feedback mechanisms.
  • Design and implement human-in-the-loop processes that balance automation with transparency, control, and reliability.
  • Drive experimentation and validation efforts to assess model performance, mitigate risk, and support data-informed product decisions.
  • Define, monitor, and optimize product KPIs and machine learning performance metrics to ensure measurable business impact.
  • Communicate complex technical concepts, machine learning systems, and optimization strategies effectively to both technical and non-technical stakeholders.
Requirements
  • Minimum of 5 years of product management experience, including several years working with machine learning, artificial intelligence, predictive systems, or algorithmic decision-making products.
  • Proven experience collaborating with Data Science and Engineering teams to deliver ML-powered products and translate business needs into technical solutions.
  • Strong analytical mindset with expertise in experimentation, hypothesis testing, performance measurement, and data-driven decision-making.
  • Ability to evaluate complex business and commercial trade-offs while balancing customer, operational, and organizational priorities.
  • Solid technical fluency, including familiarity with data pipelines, model development lifecycles, model evaluation techniques, system constraints, and experimentation methodologies.
  • Experience working in highly strategic, ambiguous, and cross-functional product environments where solutions require significant discovery and iteration.
  • Excellent stakeholder management and relationship-building skills, with the ability to align diverse teams around common objectives.
  • Structured and outcome-oriented approach to product discovery, roadmap development, prioritization, and execution.
  • Exceptional communication skills with the ability to simplify and explain complex systems to varied audiences.
  • Experience with marketplaces, recommendation systems, ranking algorithms, pricing systems, advertising technology, or similar optimization-focused domains is highly desirable.
  • Passion for artificial intelligence, intelligent systems, sustainability, and creating measurable business value through technology.
Benefits
  • Fully remote work environment with flexibility to work from anywhere within eligible European locations.
  • Flexible working hours and a high level of autonomy over work organization and schedule management.
  • Dedicated learning and development budget to support professional growth through courses, certifications, conferences, and training opportunities.
  • Access to professional coaching, personal development resources, and mental health support services.
  • Regular internal workshops, knowledge-sharing sessions, and cross-functional learning opportunities.
  • Opportunity to participate in company-wide gatherings, team-building events, workshops, and collaborative office weeks throughout the year.
  • Inclusive, feedback-driven culture that encourages innovation, experimentation, and continuous improvement.
  • Collaborative and diverse international team environment with strong emphasis on personal ownership and impact.
  • Optional access to modern office facilities for in-person collaboration and networking.
  • Strong commitment to work-life balance and employee well-being.
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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