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Remote Machine Learning Postdoc Jobs (NOW HIRING)

We're looking for a senior-level Machine Learning Engineer who can move quickly while maintaining ... We're remote-first, flexible, and distributed across North and South America, bringing together ...

We're looking for a senior-level Machine Learning Engineer who can move quickly while maintaining ... We're remote-first, flexible, and distributed across North and South America, bringing together ...

We're looking for a senior-level Machine Learning Engineer who can move quickly while maintaining ... We're remote-first, flexible, and distributed across North and South America, bringing together ...

Senior Machine Learning Engineer

$125K - $165K/yr

This is a fully remote position, allowing you to work from home or location of record within the U ... Senior Engineer Machine Learning Position Overview Paylocity is growing its Machine Learning ...

This is a fully remote position, allowing you to work from home or location of record within the U ... Our machine learning engineering team is responsible for developing infrastructure and tooling to ...

This role is fully remote within the US** What You'll Do * Build and scale machine-learning driven features across multiple products * Design reusable architecture that powers and accelerates machine ...

Approval of remote and hybrid work is not guaranteed regardless of work location.For additional ... Quantum Machine Learning and AI: Develop novel quantum algorithms and computational frameworks for ...

Showing results 41-60

Remote Machine Learning Postdoc information

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 key skills and qualifications needed to thrive as a remote machine learning postdoc?

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.
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What are the most commonly searched types of Machine Learning Postdoc jobs?

The most popular types of Machine Learning Postdoc jobs are:

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States with the most job openings for Remote Machine Learning Postdoc jobs include:

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For Remote Machine Learning Postdoc jobs, the most frequently searched job titles are:

Infographic showing various Remote Machine Learning Postdoc job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 74% Full Time, 22% Part Time, and 2% Contract. Highlights an 82% Physical, 2% Hybrid, and 16% Remote job distribution.

AI/Machine Learning Engineer

Remote

Initiate Government Solutions, LLC.
IT ServicesΒ β€’Β 11 - 50 employees

Full-time

Re-posted 6 days ago


Job description

Job Summary:
Initiate Government Solutions (IGS) is a fully remote IT services provider focused on delivering innovative solutions in the federal sector. They are seeking an AI/Machine Learning Engineer to support the development of AI applications in the federal healthcare industry, working collaboratively with a team to accelerate digital transformation through scalable AI solutions.
Responsibilities:
β€’ Design, develop, and deploy machine learning and deep learning models to support clinical decision-making, predictive analytics, and health outcomes research.
β€’ Fine-tune models for high performance using healthcare-specific data, including EHRs, claims, imaging, and structured/unstructured text.
β€’ Collaborate with data engineers to clean, preprocess, and normalize healthcare data in compliance with federal data standards (e.g., HL7, FHIR).
β€’ Build scalable ML pipelines that integrate with federal data platforms and cloud services (e.g., VA’s Lighthouse API, Azure Government, AWS GovCloud).
β€’ Ensure AI/ML solutions meet federal regulations, including HIPAA, FISMA, FedRAMP, and VA Information Security requirements.
β€’ Implement differential privacy, encryption, and access controls to safeguard sensitive health data.
β€’ Contribute to the development of governance frameworks to ensure transparent, explainable, and bias-mitigated models.
β€’ Document model lifecycle, from training to deployment, including risk assessments, validation reports, and audit trails.
β€’ Work cross-functionally with program managers, clinicians, data scientists, and software developers to identify opportunities for AI/ML applications that improve healthcare delivery and veteran outcomes.
β€’ Present complex machine learning findings in a way that is actionable and aligned with federal healthcare program goals.
β€’ Stay updated on the latest developments in AI/ML applications for public health and healthcare operations.
β€’ Prototype and test emerging AI technologies (e.g., NLP for clinical text, computer vision for imaging diagnostics) for possible integration into government systems.
β€’ Monitor deployed models for drift, accuracy, and operational effectiveness over time.
β€’ Maintain model retraining schedules based on new data inputs or policy changes.
β€’ Prepare comprehensive documentation and reports for internal stakeholders and external oversight (e.g., OMB, GAO, IG audits).
β€’ Develop dashboards and visualizations to track performance metrics, patient outcomes, and utilization trends impacted by AI/ML tools.
Qualifications:
Required:
β€’ Bachelor’s degree or higher in one of the following disciplines, Computer Science, Data Science, Artificial Intelligence / Machine Learning, Mathematics / Statistics, Biomedical Engineering, Health Informatics, Electrical or Computer Engineering
β€’ 4+ years of experience in software and machine learning engineering.
β€’ Strong knowledge of natural language processing (NLP) and transformer models.
β€’ 5+ years proficiency in Python and hands-on experience with ML libraries like TensorFlow, PyTorch, or Hugging Face Transformers.
β€’ Proven experience building scalable, cloud-based AI/ML solutions and enhancing custom question answering mapping/workflows.
β€’ Expertise in the full ML pipeline, including data processing, model training, serving, and monitoring.
β€’ Knowledge of NLP architectural strategies such as Retrieval-Augmented Generation, Knowledge Graphs, and Agentic Graphs.
β€’ Expertise in MLOps best practices, including Infrastructure as Code (IaC), CI/CD pipelines tailored for ML workflows, model version control, and real-time performance monitoring to ensure scalable and reliable AI/ML systems.
β€’ Familiarity with federal AI governance frameworks and compliance standards (e.g., NIST AI RMF, FedRAMP) is a plus.
β€’ Passion for developing team-oriented solutions to complex engineering problems
β€’ Excellent communication skills and attention to detail
β€’ Analytical mind and problem-solving aptitude
β€’ Ability to obtain and maintain a Public Trust
β€’ Strong organizational skills
Preferred:
β€’ Master’s degree in one of the above-mentioned fields
β€’ Preferred Tools & Environments: Python, R, TensorFlow, PyTorch, Scikit-learn, AWS (SageMaker), Azure ML, Databricks, Apache Spark, Power BI, Tableau, Plotly, Git, GitHub/GitLab
β€’ Active VA Public Trust
β€’ Prior experience supporting a VA program
β€’ Prior, successful experience working in a remote environment
Company:
IGS is a solutions provider, partnering with the Federal Government to tackle the most challenging issues, including interoperability, data analytics, business/clinical applications and operations, and program/project management. Founded in 2007, the company is headquartered in West Palm Beach, USA, with a team of 51-200 employees. The company is currently Growth Stage.