Monday-Wednesday in Grand Rapids MI Corporate office, Thursday-Friday remote. What You'll be Doing ... Expertise in machine learning and AI frameworks (TensorFlow, PyTorch, scikit-learn or equivalent)
New
Monday-Wednesday in Grand Rapids MI Corporate office, Thursday-Friday remote. What You'll be Doing ... Expertise in machine learning and AI frameworks (TensorFlow, PyTorch, scikit-learn or equivalent)
New
Advisory Services Analyst - State Health & Medicaid (Remote Eligible)
Ann Arbor, MI · On-site +1
$70K - $90K/yr
Familiarity with AI, machine learning concepts, or AI-enabled analytic tools and an understanding of their appropriate use in policy research and data analysis environments * Excellent written and ...
Advisory Services Analyst - State Health & Medicaid (Remote Eligible)
Ann Arbor, MI · On-site +1
$70K - $90K/yr
Familiarity with AI, machine learning concepts, or AI-enabled analytic tools and an understanding of their appropriate use in policy research and data analysis environments * Excellent written and ...
Senior AI Engineer
Grand Rapids, MI · On-site +1
$100K - $137K/yr
We offer unlimited PTO, a flexible remote work policy, and a supportive environment that ... The Senior AI Engineer 1 (Senior Staff) leads the development of advanced AI and machine learning ...
Senior AI Engineer
Grand Rapids, MI · On-site +1
$100K - $137K/yr
We offer unlimited PTO, a flexible remote work policy, and a supportive environment that ... The Senior AI Engineer 1 (Senior Staff) leads the development of advanced AI and machine learning ...
OEM Sales Director-Machinery
MI · On-site +1
This role can be remote in the United States and supports the Motion Drive Products Division in New ... Our Team Dynamics Our teams support each other, collaborate, and never stop learning. Everyone ...
OEM Sales Director-Machinery
MI · On-site +1
This role can be remote in the United States and supports the Motion Drive Products Division in New ... Our Team Dynamics Our teams support each other, collaborate, and never stop learning. Everyone ...
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.
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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:
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Full-time
Posted yesterday
New
Meijer rating
6.2
Based on 1,607 frontline employees who took The Breakroom Quiz
20th of 39 rated national retailers
Job description
As a family company, we serve people and communities. When you work at Meijer, you're provided with career and community opportunities centered around leadership, personal growth and development. Consider joining our family - take care of your career and your community!
Meijer Rewards
Weekly pay
Scheduling flexibility
Paid parental leave
Paid education assistance
Team member discount
Development programs for advancement and career growth
Please review the job profile below and apply today!
Position will follow our hybrid schedule: Monday-Wednesday in Grand Rapids MI Corporate office, Thursday-Friday remote.What You'll be Doing:
Data Engineering, Analytics & AI/Automation
Lead the design, development, and implementation of data engineering, analytics, and AI/automation solutions to support business objectives.
Oversee data architecture, ensuring data integrity, security, and scalability.
Manage and mentor a team of data engineers, data scientists, and analysts, fostering a culture of collaboration and continuous improvement.
Collaborate with cross-functional teams to identify data needs and develop strategies to leverage data for business insights and decision-making.
Drive adoption of best practices in data management, analytics, and AI/automation.
Ensure compliance with data governance policies and regulations.
Stay current with industry trends and emerging technologies in data engineering, analytics, and AI/automation.
Develop and manage budgets, resources, and timelines for data projects.
Ensure all teams follow engineering and IT standards for change controls and IT practices for production systems.
Enterprise Quality Adoption
Own the enterprise quality strategy - embed quality into the software development lifecycle, not onto it.
Drive adoption of test automation, shift-left testing, and continuous quality practices across all engineering teams.
Define and enforce quality standards, frameworks, and tooling across the portfolio; ensure consistent adoption at scale.
Partner with engineering and product teams to establish quality gates that protect production stability without slowing delivery.
Report on quality health across domains, with clear visibility into defect rates, test coverage, and release readiness.
Engineering Delivery Performance - DORA Metrics
Establish DORA metrics (Deployment Frequency, Lead Time for Changes, Change Failure Rate, Mean Time to Recovery) as the standard measurement framework for engineering delivery health.
Own the baseline, targets, and reporting cadence for DORA metrics across teams; surface trends to senior leadership with clear business context.
Use DORA data to identify delivery bottlenecks, prioritize platform and process investments, and demonstrate improvement over time.
Connect engineering performance to business outcomes - faster delivery and lower failure rates translate directly to customer experience and cost efficiency at Meijer's scale.
Partner with DevOps and platform teams to build the tooling and observability infrastructure required to measure and improve DORA outcomes.
IT General Controls (ITGC)
Accountable for ITGC compliance across the technology domains in scope - change management, access controls, computer operations, and program development controls.
Partner with Internal Audit, Compliance, and Finance to ensure controls are designed, operating effectively, and audit-ready.
Own remediation of ITGC deficiencies; drive root cause analysis and sustainable control improvements rather than point-in-time fixes.
Ensure all teams understand and operate within ITGC requirements as a standard part of the delivery process - not a compliance afterthought.
Maintain documentation, evidence, and control narratives sufficient to support SOX and internal audit cycles.
What You Bring with You (Qualifications):
Education
Bachelor's degree in Computer Science, Information Technology, Data Science, or a related field. Master's degree preferred.
Experience
10+ years of experience in data engineering, analytics, and AI/automation, with at least 5 years in a leadership role.
Proven experience establishing and scaling enterprise quality practices across large engineering organizations.
Hands-on experience implementing DORA metrics programs and using delivery performance data to drive engineering improvement.
Demonstrated experience with ITGC compliance, SOX controls, or equivalent control frameworks in an enterprise environment.
Track record of managing multiple complex programs simultaneously in a fast-paced, high-scale environment.
Technical Skills
Strong knowledge of data architecture, data warehousing, ETL processes, and data modeling.
Proficiency in Python, Java, or Scala; experience with big data technologies including Spark, Kafka, and Databricks.
Expertise in machine learning and AI frameworks (TensorFlow, PyTorch, scikit-learn or equivalent).
Familiarity with CI/CD tooling, test automation frameworks, and observability platforms used to track delivery and quality metrics.
Working knowledge of ITGC control domains: logical access, change management, computer operations, and program development.
Leadership & Communication
Strong communication and interpersonal skills; able to collaborate with and influence stakeholders at all levels.
Speaks the language of business outcomes - connects technology performance to cost, revenue, and customer experience.
Proven ability to manage multiple priorities and drive accountability across matrixed teams.