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Flexible Machine Learning Engineer Biotech Jobs in Virginia

Machine Learning Engineer Richmond, Virginia (5 Days Onsite) need local within commute About the Role We are seeking a Machine Learning Engineer with expertise in agentic AI systems to design, build ...

Machine Learning Engineer

Arlington, VA · On-site

$77K - $176K/yr

R0246231 Machine Learning Engineer The Opportunity: As an experience d AI and ML engineer, you know that machine learning is critical to understanding and processing massive datasets. Your ability to ...

Machine Learning Engineer

Ashburn, VA · On-site

$117K - $140K/yr

We are seeking a Machine Learning Engineer to join our team and support our client in Ashburn, VA ... Flexible in working extended hours.The above statements are intended to describe the general nature ...

Machine Learning Engineer

Mclean, VA · On-site

$105K - $115K/yr

Flexible PTO * Professional development : CEU and tuition reimbursement How You'll Make an Impact ... As a Machine Learning Engineer at Somatus, you will work collaboratively with our data and ...

Machine Learning Engineer General Information Requisition #728 Locations USA-VA-Chantilly Posting Date 07/24/2026 Security Clearance Required - TS/SCI + CI Poly Remote Type N/A Time Type Full time ...

... flexible, and high-quality technical solutions. In This Position You Will: * Collaborate with ... Machine learning experience using visual data * Understanding of a variety of machine learning ...

Machine Learning Engineer

Arlington, VA · Hybrid

$110K - $200K/yr

... flexible, and high-quality technical solutions. In This Position You Will: * Collaborate with ... Machine learning experience using visual data * Understanding of a variety of machine learning ...

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Showing results 41-60

Flexible Machine Learning Engineer Biotech information

What is the difference between Flexible Machine Learning Engineer Biotech vs Data Scientist Biotech?

AspectFlexible Machine Learning Engineer BiotechData Scientist Biotech
Required CredentialsDegree in Computer Science, Data Science, or related fields; experience with ML frameworksDegree in Statistics, Mathematics, or related fields; proficiency in data analysis
Work EnvironmentDevelops and deploys ML models in biotech R&D and production settingsAnalyzes biological data to extract insights, often in research labs or biotech companies
Employer & Industry UsageUsed by biotech firms focusing on AI-driven drug discovery and diagnosticsCommon in biotech research, clinical data analysis, and bioinformatics

The main difference is that a Flexible Machine Learning Engineer Biotech primarily develops and implements machine learning models tailored for biotech applications, while a Data Scientist Biotech focuses on analyzing biological data to generate insights. Both roles require strong technical skills, but the engineer emphasizes model deployment and integration, whereas the scientist emphasizes data interpretation and statistical analysis.

What are the most commonly searched types of Machine Learning Engineer Biotech jobs in Virginia?

The most popular types of Machine Learning Engineer Biotech jobs in Virginia are:

What are popular job titles related to Flexible Machine Learning Engineer Biotech jobs in Virginia?

For Flexible Machine Learning Engineer Biotech jobs in Virginia, the most frequently searched job titles are:

What cities in Virginia are hiring for Flexible Machine Learning Engineer Biotech jobs?

Cities in Virginia with the most Flexible Machine Learning Engineer Biotech job openings:

Infographic showing various Flexible Machine Learning Engineer Biotech job openings in Virginia as of August 2026, with employment types broken down into 1% As Needed, 71% Full Time, 25% Part Time, and 3% Contract. Highlights an 82% Physical, 1% Hybrid, and 17% Remote job distribution.

Machine Learning Engineer - Autonomy

Heven AeroTech

Sterling, VA • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 6 days ago


Job description

Title: Machine Learning Engineer, Autonomy
Company: Heven AeroTech
Location: Bingen, Washington or Sterling, Virginia
FLSA: Exempt

About Our Company:

At Heven AeroTech (Heven), we don't just believe in the power of people-we build our success on it. As a recognized leader in hydrogen-powered drones, we've earned recognition for creating a workplace where innovation thrives, collaboration is second nature, and every employee feels valued. Our culture is anchored in trust and a shared commitment to excellence.

We believe great teams are built on individuals who are humble, hungry, and smart-those who put team success first, take initiative to continuously improve, and demonstrate strong interpersonal awareness. At Heven, your voice matters, your ideas are heard, and your contributions make a tangible impact as you grow through hands-on experience and collaboration across the team.

Role Summary:
Reporting to the Head of Mission Systems and Software, the Machine Learning Engineer - Autonomy develops and deploys machine learning and autonomy capabilities for Heven AeroTech uncrewed aircraft systems. The role focuses on practical UAS autonomy, including perception, tracking, sensor fusion, mission-level decision making, planning, and integration with flight-control, mission-system, onboard-compute, and payload interfaces. This engineer works closely with other Machine Learning Engineers, Platform Engineers, Flight Test, and aircraft engineering teams to take autonomy capabilities from development through simulation, integration, ground test, and flight test.

Essential Responsibilities:

  • Develop, integrate, and deploy machine learning and autonomy capabilities for uncrewed aircraft, with emphasis on reliable operation on real aircraft and onboard compute.
  • Develop mission-level autonomous behaviors using appropriate combinations of state machines, behavior trees, planners, optimization methods, deterministic logic, and machine learning.
  • Develop and integrate perception capabilities including object detection, classification, tracking, scene understanding, sensor fusion, and geospatial reasoning.
  • Integrate autonomy software with autopilots, companion computers, mission computers, sensors, payloads, data links, and GCS/C2 systems while maintaining clear interfaces with flight-control functions.
  • Develop production-quality C++ and Python software for real-time and near-real-time execution, including optimization for NVIDIA GPU and embedded edge-compute platforms.
  • Develop and use simulation, SIL, HIL, bench-test, and automated test environments to evaluate autonomy behavior and reduce risk prior to flight.
  • Support aircraft integration, ground test, and flight test of autonomy capabilities, including analysis of logs and test data to characterize performance and drive improvements.
  • Collaborate across Heven AeroTech with Machine Learning Engineers, Platform Engineers, Flight Test, avionics, electrical, mechanical, and other engineering teams.

Qualifications & Experience:

Required:

  • BA/BS degree in Computer Science, Electrical Engineering, Robotics, Aerospace Engineering, or a related technical field, or equivalent practical experience.
  • 2-5 years of experience developing and deploying machine learning or autonomy software on robotic, autonomous, or UAS platforms.
  • Strong C++ and Python development skills, including Linux-based development and modern machine learning frameworks.
  • Working knowledge of perception, sensor integration, autonomous decision making or planning, and real-time system integration.
  • Professional working proficiency in English (spoken and written) is required to perform the responsibilities of this role.

Preferred:

  • Direct experience with UAS autonomy, aircraft integration, or flight test.
  • Experience with NVIDIA edge compute, CUDA/TensorRT, ROS 2, MAVLink, or comparable robotics and vehicle interfaces.
  • Aerospace or defense experience and eligibility to obtain a DoD Secret clearance.

Physical Requirements:

  • Ability to work effectively in a standard office, engineering laboratory, aircraft integration, hangar, and outdoor flight-test environment.
  • Ability to stand, walk, bend, kneel, reach, and work around aircraft, ground-support equipment, test equipment, and computing hardware for extended periods as required.
  • Ability to lift, carry, and position equipment and components weighing up to 25 pounds, with or without reasonable accommodation.
  • Ability to safely work in outdoor environments and varying weather conditions during ground and flight-test activities.
  • Ability to work around aircraft systems, electrical equipment, rotating equipment, batteries, and other laboratory/flight-test hazards while following applicable safety procedures and PPE requirements.
  • Ability to visually inspect equipment, read computer displays, instrumentation, schematics, logs, and test data, with or without reasonable accommodation.
  • Ability to work flexible hours, including early mornings, evenings, or occasional weekends, when required to support aircraft integration, ground testing, or flight-test operations.
  • Ability and willingness to travel to company facilities, customer sites, and/or designated flight-test locations as required by the position.

Benefits Overview: 
Heven AeroTech offers a competitive benefits package designed to support the health, financial security, and overall well-being of our employees and their families. Benefits include medical, dental, and vision coverage, retirement plans, paid time off/sick, and additional protections such as critical illness, hospital indemnity, accident coverage, and short- and long-term disability.

Equal Employment Opportunity Statement: 
Heven AeroTech is an Equal Opportunity Employer and considers all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other protected characteristic under applicable law.