2

Remote Machine Learning Postdoc Jobs in Washington, DC

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 ...

This is a fully remote position for candidates in the continental U.S., with work hours aligned to ... This role involves leveraging cutting-edge technologies, including GenAI and machine learning ...

Senior AI/ML Engineer

Great Falls, VA · Remote

$105K - $145K/yr

... machine learning platforms, and practical experience operationalizing AI solutions from concept to production. Location: Vienna VA (We will consider Remote candidates within US Mainland on EST ...

next page

Showing results 1-20

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 Washington, DC? The most popular types of Machine Learning Postdoc jobs in Washington, DC are:

AI Machine Learning Skill 2-FFPP-8904

Onyx Point, Inc.

Hanover, MD • On-site, Remote

$78K - $250K/yr

Other

Medical, Dental, Vision, Life, Retirement, PTO

This job post has expired 1 day ago. Applications are no longer accepted.


Job description

REQUIRED:TO BE CONSIDERED FOR THIS POSITION YOU MUST HAVE AN ACTIVE TS/SCI W/ FULL SCOPE POLYGRAPH SECURITY CLEARANCE (U.S. CITIZENSHIP REQUIRED)
The Artificial Intelligence/Machine Learning (AI/ML) Engineer designs, creates, tests, and productizes AI/ML algorithms to solve business challenges. The AI/ML models they create should be capable of learning and making predictions as defined by the business logic developed to meet customer requirements. The AI/ML Engineer should be proficient in all aspects of model architecture, data pipeline interaction, and metrics application, interpretation, and presentation. The AI/ML Engineer needs familiarity with foundational concepts of application development, infrastructure management, data engineering, and data governance. Through an understanding of training, retraining, deploying, scheduling, monitoring, and improving models through iterative user and system feedback, the AI/ML Engineer designs and creates scalable solutions for optimal performance. The AI/ML Engineer may be responsible for leading geographically diverse teams and will often serve as a primary POC for AI-related matters, so must have exceptional analytical, problem-solving and communication skills. Expert knowledge of multiple programming languages, e.g. Python, Java, C, R, a plus.
Required Skills:Five (5) years experience in applied machine learning in programs and contracts of similar scope, type, and complexity is required. A Master's or Ph.D. degree in advanced math, artificial intelligence, data science, computer science or deep learning from an accredited college or university. 5 additional years of machine learning experience with a relevant Bachelor's degree may be substituted for a Master's degree. Experience with standard machine language frameworks, e.g. Pytorch, TensorFlow.
Select appropriate data sets
Perform statistical analysis
Run machine learning algorithms
Use results to improve models
Train and retrain systems when needed
Experience in working with various ML libraries and packages
Run standard test and evaluation protocols
Provide system integration oversight
Oversee Test and evaluation of AI and ML algorithms through an iterative design process to meet verification and validation requirements
Research and implement a broad range of AI and ML algorithms and tools
Design or Select appropriate data and knowledge representation methods
Recognize software architecture, data modelling, and data structures
Transform and convert data science prototypes into scalable solutions
Verify data and model output quality
Identify differences in data distribution that affect model performanceCompensation: We are committed to providing fair and competitive compensation. The salary range for this position is $78,000 to $250,000 per year. This range reflects the compensation offered across the locations where we hire. The exact salary will be determined based on the candidate's work location, specific role, skill set, and level of expertise.Benefits: We offer a comprehensive benefits package, including:
  • Health Coverage: Medical, dental, and vision insurance
  • Additional Insurance: Basic Life/AD&D, Voluntary Life/AD&D, Short and Long-Term Disability, Accident, Critical Illness, Hospitalization Indemnity, and Pet Insurance
  • Retirement Plan: 401(k) plan with company match
  • Paid Time Off: Generous PTO, paid holidays, parental leave, and more
  • Wellness: Access to wellness programs and mental health support
  • Professional Development: Opportunities for growth, including tuition reimbursement
Additional Perks:
  • Flexible work arrangements, including remote work options
  • Flexible Spending Accounts (FSAs)
  • Employee referral programs
  • Bonus opportunities
  • Technology allowance
  • A diverse, inclusive, and supportive workplace culture