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Remote Machine Learning Postdoc Jobs in Michigan

Posting Type Remote/Hybrid Job Overview WHO WE ARE Relativity is a leading legal data intelligence ... Develop machine learning and generative AI models that ship as customer-facing product features

... AI and machine learning, and owning the key performance indicators tied to their initiatives ... We embrace a remote-first culture through our Flexible Workplace. Most employees hold Home-Flex ...

Lead Research Engineer

Ann Arbor, MI · On-site +1

$100.30K - $132.10K/yr

... remote teams. * Be an Agile Person:With a strong sense of urgency and a desire to work in a fast ... Experienceintegrating Machine Learning solutionsinto production-grade softwarewith a sound ...

This position is remote and requires a Secret security clearance. Maximus TCS (Technology and ... data for machine learning pipelines, feature engineering, and model lifecycle management ...

New

This position is remote and requires a Secret security clearance. Maximus TCS (Technology and ... data for machine learning pipelines, feature engineering, and model lifecycle management ...

New

This position is remote and requires a Secret security clearance. Maximus TCS (Technology and ... data for machine learning pipelines, feature engineering, and model lifecycle management ...

New

This position is remote and requires a Secret security clearance. Maximus TCS (Technology and ... data for machine learning pipelines, feature engineering, and model lifecycle management ...

New

This position is remote and requires a Secret security clearance. Maximus TCS (Technology and ... data for machine learning pipelines, feature engineering, and model lifecycle management ...

New

This position is remote and requires a Secret security clearance. Maximus TCS (Technology and ... data for machine learning pipelines, feature engineering, and model lifecycle management ...

New

This position is remote and requires a Secret security clearance. Maximus TCS (Technology and ... data for machine learning pipelines, feature engineering, and model lifecycle management ...

New

This position is remote and requires a Secret security clearance. Maximus TCS (Technology and ... data for machine learning pipelines, feature engineering, and model lifecycle management ...

New

This position is remote and requires a Secret security clearance. Maximus TCS (Technology and ... data for machine learning pipelines, feature engineering, and model lifecycle management ...

New

This position is remote and requires a Secret security clearance. Maximus TCS (Technology and ... data for machine learning pipelines, feature engineering, and model lifecycle management ...

New

This position is remote and requires a Secret security clearance. Maximus TCS (Technology and ... data for machine learning pipelines, feature engineering, and model lifecycle management ...

New

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Remote Machine Learning Postdoc information

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.

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 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.
What are the most commonly searched types of Machine Learning Postdoc jobs in Michigan? The most popular types of Machine Learning Postdoc jobs in Michigan are:
What are popular job titles related to Remote Machine Learning Postdoc jobs in Michigan? For Remote Machine Learning Postdoc jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Remote Machine Learning Postdoc jobs in Michigan look for? The top searched job categories for Remote Machine Learning Postdoc jobs in Michigan are:
What cities in Michigan are hiring for Remote Machine Learning Postdoc jobs? Cities in Michigan with the most Remote Machine Learning Postdoc job openings:
Machine Learning Scientist - AI Trainer

Machine Learning Scientist - AI Trainer

DataAnnotation

Lansing, MI • On-site, Remote

$60/hr

Full-time

Posted 18 days ago


Job description

Join the DataAnnotation team and contribute to developing cutting‐edge AI systems, while enjoying the flexibility of remote work and setting your own schedule. We are looking for experienced quantitative professionals to help advance AI development. AI models are increasingly capable of performing complex analytical and scientific reasoning — but these systems still need practitioners with real‐world quantitative experience to validate whether the outputs actually hold up in practice.

That's where you come in. As a member of DataAnnotation's team, you'll work closely with state‐of‐the‐art AI models on tasks like evaluating AI‐generated quantitative analysis, solving technical problems, and providing feedback that directly shapes how these systems reason about data, models, and scientific problems. Whether your background is in data science, astrophysics, economics, biostatistics, operations research, or any other quantitative field, if you think rigorously about data and models, your skills are directly applicable here.

Some team members fit this work alongside a full‐time role, while others treat it as their primary focus. To get started, once you sign up for an account, you'll take a short assessment (this serves as our version of an interview). If you pass, you'll receive an email confirmation, and paid work will become available on our platform.

Benefits Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New Zealand. Flexible schedule: choose which projects you take on and when you work. Competitive pay: projects are paid hourly, up to $60 USD/hour.

Impact: help shape the future of AI systems built to reason about data and analytics. Responsibilities Evaluate AI‐generated quantitative work, including statistical analysis, predictive modeling, scientific reasoning, and data‐driven insights, for technical accuracy and real‐world validity. Design and solve quantitative problems used to train and benchmark AI systems, spanning areas like forecasting, experimental analysis, optimization, and statistical inference.

Write clear technical explanations and well‐documented analytical code. Provide feedback that directly shapes the next generation of AI models built for quantitative reasoning. Qualifications 2+ years of hands‐on experience in a quantitative role or research environment — such as data science, statistics, economics, finance, physics, biology, epidemiology, operations research, or any adjacent field.

Some coding experience required, with comfort writing and reviewing analytical code end‐to‐end. Practical experience with statistical methods, predictive modeling, and experiment design (e.g., A/B testing, hypothesis testing, regression, classification, time‐series forecasting). Fluency in English (native or bilingual level) with strong writing skills.

A bachelor's degree in a quantitative field is preferred (Statistics, Computer Science, Mathematics, Engineering, or similar); a master's or PhD is a plus. Relevant credentials are a plus (e.g., Kaggle Competition ranking, AWS/GCP ML certifications, or equivalent demonstrated expertise). Payment is made via PayPal.

We will never ask for any money from you. This job is only available to those in the US, Canada, UK, Ireland, Australia, and New Zealand. #J-18808-Ljbffr