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Remote Bioinformatics Machine Learning Jobs in Suitland, MD

Senior Machine Learning Engineer

Arlington, VA · On-site +1

$120K - $165K/yr

As a Senior Machine Learning Engineer, you will drive hands-on engineering and modeling for Defense ... Practical knowledge of remote sensing, satellite imagery, or related geospatial domains * Knowledge ...

Machine Learning Engineer Schedule: Full-Time Shift: Day Job Travel: Yes - 10% of the time Minimum ... None Potential for Remote Work: ORA_HYBRID Description We are seeking to build a team of AI/ML ...

New

Maintain current in emerging tools and techniques in machine learning, statistical modeling, and ... Washington DC Metro Area - Remote (candidates MUST BE located in the National Capital Region - DMV ...

Maintain current in emerging tools and techniques in machine learning, statistical modeling, and ... Washington DC Metro Area - Remote (candidates MUST BE located in the National Capital Region - DMV ...

Showing results 21-40

Remote Bioinformatics Machine Learning information

See Suitland, MD salary details

$64.1K

$101.8K

$161K

How much do remote bioinformatics machine learning jobs pay per year?

As of Sep 6, 2026, the average yearly pay for remote bioinformatics machine learning in Suitland, MD is $101,760.00, according to ZipRecruiter salary data. Most workers in this role earn between $72,700.00 and $139,500.00 per year, depending on experience, location, and employer.

What is a remote bioinformatics machine learning specialist?

A Remote Bioinformatics Machine Learning specialist is a professional who applies machine learning techniques to biological data, such as genomics or proteomics, while working from a remote location. They analyze complex biological datasets to uncover patterns, make predictions, and contribute to advancements in areas like drug discovery, disease research, and personalized medicine. These specialists typically have strong skills in programming, statistics, biology, and data analysis, and collaborate with researchers and healthcare professionals through digital communication tools.

What are the key skills and qualifications needed to thrive as a remote bioinformatics machine learning specialist?

To excel as a Remote Bioinformatics Machine Learning Specialist, a strong background in computational biology, statistics, and machine learning—often supported by an advanced degree in bioinformatics, computer science, or a related field—is essential. Proficiency with programming languages like Python or R, experience using machine learning frameworks (such as TensorFlow or scikit-learn), and familiarity with bioinformatics tools and databases are typically required. Excellent problem-solving, self-motivation, and clear communication skills help professionals collaborate effectively and independently in remote environments. These abilities are vital for developing accurate models, interpreting complex biological data, and contributing meaningful insights to scientific research.

How do remote bioinformatics machine learning professionals typically collaborate with cross-functional teams?

Remote bioinformatics machine learning professionals often work closely with biologists, data scientists, and software engineers. Collaboration is typically facilitated through virtual meetings, shared code repositories, and project management tools. Regular communication is essential to align on data requirements, model development, and interpretation of results. While remote work offers flexibility, it requires strong organizational skills and proactive engagement to ensure seamless teamwork and project success.

What is the difference between Remote Bioinformatics Machine Learning vs Remote Computational Biologist?

AspectRemote Bioinformatics Machine LearningRemote Computational Biologist
Required CredentialsMaster's or PhD in Bioinformatics, Computer Science, or related fields; experience in machine learningMaster's or PhD in Biology, Bioinformatics, or related fields; strong computational skills
Work EnvironmentRemote, collaborative teams in biotech, pharma, or research institutionsRemote or on-site, working in research labs or academic settings
Industry UsageUsed in biotech, healthcare, and pharmaceutical industries for data analysis and model developmentCommon in academic research, biotech, and healthcare for biological data interpretation

Remote Bioinformatics Machine Learning focuses on developing algorithms and models to analyze biological data using machine learning techniques. In contrast, Remote Computational Biologist applies computational methods to biological research questions, often integrating diverse data types. Both roles require strong computational skills and often overlap, but the former emphasizes machine learning expertise, while the latter has a broader biological research scope.

What job categories do people searching Remote Bioinformatics Machine Learning jobs in Suitland, MD look for?

The top searched job categories for Remote Bioinformatics Machine Learning jobs in Suitland, MD are:

What cities near Suitland, MD are hiring for Remote Bioinformatics Machine Learning jobs?

Cities near Suitland, MD with the most Remote Bioinformatics Machine Learning job openings:

Senior Machine Learning Engineer

Planet

Arlington, VA • On-site, Remote

$120K - $165K/yr

Full-time, Part-time

Medical, Dental, Vision, PTO

Posted 8 days ago


Key responsibilities

  • Drive hands-on engineering and modeling for geospatial analytics, including implementing novel embeddings-based change detection and advanced computer vision techniques.

  • Ensure best-in-class testing, validation, and deployment of models to run at continental and global scales.

  • Collaborate with data scientists and software engineers to define requirements, iterate on algorithm designs, and integrate ML pipelines with software platforms.


Job description

About the Role:

Planet's Analytics Team for Global Monitoring focuses on novel geospatial and time series analytics for customers requiring robust change detection, object detection, and generative AI capabilities. As a Senior Machine Learning Engineer, you will drive hands-on engineering and modeling for Defense and Intelligence applications. You'll implement novel embeddings-based change detection and advanced computer vision techniques. In this role, you will ensure best-in-class testing and deploy solutions to run at continental and global scales. You'll collaborate closely with data scientists and software engineers to drive innovation in remote sensing and large-scale geospatial analytics. Ideal candidates bring a creative mindset and passion for solving complex geospatial challenges.

This is a full-time, hybrid role which will require you to work from our Arlington, VA office 3 days per week.

Impact You'll Own:

  • Spearhead the development of novel algorithms and machine learning models tailored for Defense and Intelligence applications.
  • Optimize model performance to execute high-throughput inference at continental and global scales.
  • Innovate computer vision, time series, and embeddings-based techniques to uncover new insights from satellite data.
  • Collaborate with product managers, data scientists, and engineers to define requirements and iterate on algorithm designs.
  • Integrate ML pre-processing and inference pipelines seamlessly with adjacent software engineering platforms.
  • Establish best-in-class testing, validation, and monitoring frameworks for continuous model reliability.

What You Bring:

  • 10+ years of relevant experience of which 6+ years of experience is in machine learning.
  • Ability to conduct a rigorous evaluation of results and internal communication of algorithm failure modes.
  • Expertise with data science, time series methods, computer vision, and embeddings. 
  • Ability to implement, train, and optimize neural networks.
  • Experience wrangling large datasets, ideally with geospatial libraries, combined with frameworks like PyTorch/TF for model development and training.
  • Ability to experiment with model architectures, and derive data-driven insights to iteratively improve performance and accuracy.
  • Experience writing clean, modular Python code and applying software development best practices (Git, testing, CI/CD).
  • Experience deploying models (via Docker, Kubernetes, or similar) with an understanding of best practices for monitoring and maintaining them at scale.
  • AWS or GCP experience
  • Excellent communication skills, capable of explaining technical topics to diverse audiences.
  • Graduate degree in a STEM or analytics-focused field or equivalent work experience.
  • Located in the Washington, DC metro or ability to work and commute to Arlington, VA 3x/week
  • Ability to obtain and maintain US Security Clearance

What Makes You Stand Out:

  • Practical knowledge of remote sensing, satellite imagery, or related geospatial domains
  • Knowledge of coordinate reference systems, geometry manipulations, and common data formats (GeoTIFF, GeoJSON, etc).
  • Hands-on experience building geospatial or sensor-driven data products from scratch
  • Familiarity with techniques like model compression, GPU optimizations, or distributed training pipelines

Application Deadline:

November 20, 2026 at 11:59p PT

EAR/ITAR Requirements:

This position requires access to export-controlled information, and as such, employment (or hiring of a contractor) is contingent upon the candidate's ability to access all applicable export-controlled information without additional export licensing being required by the Bureau of Industry and Security and/or the Directorate of Defense Trade Controls.

Benefits While Working at Planet:

These offerings are dependent on employment type and geographical location, based upon applicable law or company policy.

  • Comprehensive Medical, Dental, and Vision plans
  • Health Savings Account (HSA) with a company contribution
  • Generous Paid Time Off in addition to holidays and company-wide days off 
  • 16 Weeks of Paid Parental Leave
  • Wellness Program and Employee Assistance Program (EAP)
  • Home Office Reimbursement
  • Monthly Phone and Internet Reimbursement
  • Tuition Reimbursement and access to LinkedIn Learning
  • Equity
  • Commuter Benefits (if local to an office)
  • Volunteering Paid Time Off

Compensation:

The US base salary range for this full-time position at the commencement of employment is listed below. Additionally, this role might be eligible for discretionary short-term and long-term incentives (bonus and equity). The final salary range is determined by job related experience, skills and location. The range displays our typical hiring range for new hire salaries in US locations only. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.