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Remote Machine Learning Postdoc Jobs in Virginia

Machine Learning Engineer - Remote

Vienna, VA · On-site +1

$140K - $150K/yr

Halvik is a highly successful WOB business with more than 50 prime contracts and 500+ professionals delivering Digital Services, Advanced Analytics, Artificial Intelligence/Machine Learning ...

Remote Work: Niyam understands the value of flexibility. We offer remote work. * Career Growth ... The ideal candidate brings a strong foundation in machine learning, data engineering, and MLOps ...

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 ...

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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.
What are the most commonly searched types of Machine Learning Postdoc jobs in Virginia? The most popular types of Machine Learning Postdoc jobs in Virginia are:
What cities in Virginia are hiring for Remote Machine Learning Postdoc jobs? Cities in Virginia with the most Remote Machine Learning Postdoc job openings:
Machine Learning Engineer - Remote

Machine Learning Engineer - Remote

Halvik

Vienna, VA • On-site, Remote

$140K - $150K/yr

Full-time

Re-posted 8 days ago


Job description

Halvik Corp delivers a wide range of services to 13 executive agencies and 15 independent agencies. Halvik is a highly successful WOB business with more than 50 prime contracts and 500+ professionals delivering Digital Services, Advanced Analytics, Artificial Intelligence/Machine Learning, Cyber Security and Cutting Edge Technology across the US Government. Be a part of something special!
Role and Responsibilities
Model Development
  • Collaborate with data scientists and SMEs to develop ML models using curated datasets.
  • Conduct experiments, prototypes, and proof-of-concepts to validate model performance.
  • Create scalable and reusable training pipelines using Databricks notebooks and MLflow.

Implementation and Optimisation
  • LLMs (Large Language Models), RAGs, and AI agent systems for various business applications. Deployment & MLOps
  • Operationalize models with robust CI/CD workflows.
  • Deploy models usingMLflow, SageMaker, or custom APIs.
  • Monitor production models for accuracy, drift, and latency; manage retraining schedules.

Data Integration & Architecture Alignment
  • Work closely with Data Engineering to align ML pipelines with the Bronze, Silver, Gold layers of a Medallion Architecture.
  • Engineer high-quality features and maintain training/inference pipelines.

Cloud and Platform Engineering
  • Leverage AWS services including S3, EC2, Lambda, SageMaker, and Step Functions.

Collaboration & Documentation
  • Document ML artifacts, processes, and performance outcomes.
  • Contribute to agile project ceremonies and maintain a feedback loop with stakeholders.
  • Share knowledge and mentor junior team members.

Required Skills:
  • 5+ years of experience in ML Engineering or Applied Machine Learning.
  • Strong Python skills and hands-on experience with ML libraries (e.g., scikit-learn, XGBoost, PyTorch, TensorFlow).
  • Proficient with Databricks, MLflow, and PySpark.
  • Solid understanding of model lifecycle and MLOps practices.
  • Experience with AWS-based data infrastructure and related DevOps practices.
  • Demonstrated ability to productionize models and integrate with business system
  • Strong understanding of mathematics and statistics relevant to machine learning and AI.
  • Proven experience with machine learning models and algorithms (supervised, unsupervised, deep learning, etc.).
  • Solid background in software engineering principles and best practices.
  • Hands-on experience with model training frameworks (e.g., TensorFlow, PyTorch, Hugging Face).
  • Experience with MLOps tools and workflows, particularly on AWS (SageMaker, Lambda, S3, etc.).
  • Practical experience with LLMs, RAGs, and AI agent architectures.
  • Proficiency with the Databricks platform for data engineering and ML pipelines.
  • Advanced programming skills in Python.
  • Excellent communication and teamwork abilities.

Preferred Skills:
  • Experience building and deploying interactive UIs for AI models using Streamlit, Gradio, or similar frameworks for rapid prototyping and real-time model interactions
  • Business acumen and ability to align AI solutions with organizational goals.
  • Optimize compute and storage resources for performance and cost-efficiency.

Halvik's pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.
Halvik Corp is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status.
Halvik's pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.