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Flexible Machine Learning Engineer Biotech Jobs in Virginia

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Machine Learning Engineer

Reston, VA

Machine Learning Engineer Location: Fort Meade, MD Required Clearance : TS/SCI w/ Full-Scope Poly Salary: Competitive We are seeking a highly skilled and motivated Machine Learning Engineer to join ...

Samprasoft

Machine Learning Engineer

Mclean, VA

GCP/AWS Machine Learning Engineer Freddie Mac iLab is currently looking for Machine Learning Engineers in its Innovation Labs - Tech Strategy team. In this position, you will be responsible for ...

Cymertek

Machine Learning Engineer

Vienna, VA

Machine Learning Engineer LOCATION Tysons, VA 22182 CLEARANCE TS/SCI Full Poly (Please note this ... Flexible Work Schedule * Cafeteria Style Benefits * 10% - 401k Matching (Vested Immediately)

Cymertek

Machine Learning Engineer

Reston, VA

Machine Learning Engineer LOCATION Reston, VA 20190 CLEARANCE TS/SCI Full Poly (Please note this ... Flexible Work Schedule * Cafeteria Style Benefits * 10% - 401k Matching (Vested Immediately)

Cymertek

Machine Learning Engineer

Reston, VA · On-site

Machine Learning Engineer LOCATION Reston, VA 20190 CLEARANCE TS/SCI Full Poly (Please note this ... Flexible Work Schedule * Cafeteria Style Benefits * 10% - 401k Matching (Vested Immediately)

ICONMA

Machine Learning Engineer

Mclean, VA

Machine Learning Engineer Our client, a financial company, is looking for a Machine Learning Engineer for their McLean, VA location. Requirements: * Python, AWS, Kubernetes, Kubeflow, MLOps, ML ...

Cymertek

Machine Learning Engineer

Chantilly, VA

Machine Learning Engineer LOCATION Chantilly, VA 20151 CLEARANCE TS/SCI Full Poly (Please note this ... Flexible Work Schedule * Cafeteria Style Benefits * 10% - 401k Matching (Vested Immediately)

Cymertek

Machine Learning Engineer

Tysons, VA · On-site

Machine Learning Engineer LOCATION Tysons, VA 22182 CLEARANCE TS/SCI Full Poly (Please note this ... Flexible Work Schedule * Cafeteria Style Benefits * 10% - 401k Matching (Vested Immediately)

Cymertek

Machine Learning Engineer

Chantilly, VA · On-site

Machine Learning Engineer LOCATION Chantilly, VA 20151 CLEARANCE TS/SCI Full Poly (Please note this ... Flexible Work Schedule * Cafeteria Style Benefits * 10% - 401k Matching (Vested Immediately)

ManTech

Machine Learning Engineer

Herndon, VA

The Machine Learning Engineer will leverage their strong technical background and knowledge to support highly scalable machine learning-based applications, including both pipelines and services ...

Cymertek

Machine Learning Engineer

Tysons, VA

Machine Learning Engineer LOCATIONTysons, VA 22182 CLEARANCETS/SCI Full Poly (Please note this ... Flexible Work Schedule * Cafeteria Style Benefits * 10% - 401k Matching (Vested Immediately)

Cymertek

Machine Learning Engineer

Chantilly, VA

Machine Learning Engineer LOCATIONChantilly, VA 20151 CLEARANCETS/SCI Full Poly (Please note this ... Flexible Work Schedule * Cafeteria Style Benefits * 10% - 401k Matching (Vested Immediately)

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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.

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Flexible Machine Learning Engineer Biotech jobs near you

Machine Learning Engineer

Full Scope

Reston, VA

Other

Posted yesterday

Job description

Job Title:Machine Learning Engineer
Location:Fort Meade, MD
Required Clearance: TS/SCI w/ Full-Scope Poly
Salary:Competitive
We are seeking a highly skilled and motivated Machine Learning Engineer to join our dynamic team. The ideal candidate will have a strong background in machine learning, data science, and software engineering. You will work closely with data scientists, engineers, and product managers to design, develop, and deploy machine learning models and solutions that drive business value.
Key Responsibilities:
  • Design, develop, and implement machine learning models and algorithms to solve real-world problems.
  • Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.
  • Conduct data analysis and preprocessing to ensure high-quality data for model training.
  • Optimize and fine-tune models for performance, accuracy, and scalability.
  • Deploy machine learning models into production and monitor their performance.
  • Develop and maintain machine learning pipelines and infrastructure.
  • Stay current with the latest research and advancements in machine learning and AI.
  • Participate in code reviews, team meetings, and contribute to a collaborative development environment.
  • Document processes, models, and findings comprehensively.
Qualifications:
  • Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field. Ph.D. is a plus.
  • Proven experience as a Machine Learning Engineer or in a similar role.
  • Strong proficiency in programming languages such as Python, R, or Java.
  • Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn, etc.
  • Solid understanding of machine learning algorithms, including supervised and unsupervised learning, reinforcement learning, and deep learning.
  • Experience with data processing tools like Pandas, NumPy, and data visualization tools such as Matplotlib or Seaborn.
  • Familiarity with cloud platforms like AWS, Google Cloud, or Azure for model deployment and scaling.
  • Strong problem-solving skills and the ability to think critically and analytically.
  • Excellent communication and teamwork skills.
Preferred Qualifications:
  • Experience with natural language processing (NLP) and computer vision.
  • Familiarity with big data technologies such as Hadoop, Spark, or Kafka.
  • Knowledge of software development best practices and version control systems like Git.
  • Experience with containerization tools like Docker and orchestration tools like Kubernetes.
  • Previous experience in a fast-paced, startup environment.

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