2

Remote Machine Learning Postdoc Jobs in New Jersey

Remote Job Summary: In this role, you'll apply your expertise to help train next-generation AI ... Develop case strategies and motion practice templates that inform machine learning models in legal ...

Law Professor - Remote

Paterson, NJ · Remote

$100 - $150/hr

Remote Job Summary: In this role, you'll apply your expertise to help train next-generation AI ... Develop case strategies and motion practice templates that inform machine learning models in legal ...

Law Professor - Remote

Elizabeth, NJ · Remote

$100 - $150/hr

Remote Job Summary: In this role, you'll apply your expertise to help train next-generation AI ... Develop case strategies and motion practice templates that inform machine learning models in legal ...

Remote Job Summary: In this role, you'll apply your expertise to help train next-generation AI ... Develop case strategies and motion practice templates that inform machine learning models in legal ...

Law Professor - Remote

Newark, NJ · Remote

$100 - $150/hr

Remote Job Summary: In this role, you'll apply your expertise to help train next-generation AI ... Develop case strategies and motion practice templates that inform machine learning models in legal ...

Remote Job Summary: In this role, you'll apply your expertise to help train next-generation AI ... Develop case strategies and motion practice templates that inform machine learning models in legal ...

Corporate Counsel - Remote

Newark, NJ · Remote

$100 - $150/hr

Remote Job Summary: In this role, you'll apply your expertise to help train next-generation AI ... Develop case strategies and motion practice templates that inform machine learning models in legal ...

Remote Job Summary: In this role, you'll apply your expertise to help train next-generation AI ... Develop case strategies and motion practice templates that inform machine learning models in legal ...

next page

Showing results 1-20

Remote Machine Learning Postdoc information

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.

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.

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 New Jersey? The most popular types of Machine Learning Postdoc jobs in New Jersey are:
What are popular job titles related to Remote Machine Learning Postdoc jobs in New Jersey? For Remote Machine Learning Postdoc jobs in New Jersey, the most frequently searched job titles are:
What job categories do people searching Remote Machine Learning Postdoc jobs in New Jersey look for? The top searched job categories for Remote Machine Learning Postdoc jobs in New Jersey are:
What cities in New Jersey are hiring for Remote Machine Learning Postdoc jobs? Cities in New Jersey with the most Remote Machine Learning Postdoc job openings:

Reinforcement Learning Engineer

Bright Vision Technologies

North Brunswick, NJ • Remote

$100K - $150K/yr

Other

Posted 6 days ago


Job description

Bright Vision Technologies is a forward-thinking software development company dedicated to building innovative solutions that help businesses automate and optimize their operations. We leverage cutting-edge technologies to create scalable, secure, and user-friendly applications.
As we continue to grow, we’re looking for a skilled Reinforcement Learning Engineer to join our dynamic team and contribute to our mission of transforming business processes through technology.
This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential.
Reinforcement Learning Engineer
Job Title: Reinforcement Learning Engineer
Location: 100% Remote (Continental United States)
Position Type: In-house Bright Vision Technologies SOW engagement (no third-party client or vendor)
Salary: $100K - $150K / Annum
Experience: 6+ years
Sponsorship: No new H1B sponsorship available. H1B transfers welcomed for qualified candidates.
Employment Type: Full-time, direct W2 with Bright Vision Technologies (no C2C, no 1099, no third-party)
Engagement: Long-term, multi-year, aligned to the Bright Vision SOW delivery roadmap
Compensation: Competitive base salary commensurate with experience, plus benefits.
Employment Terms & Visa Policy
This is a 100% remote, full-time, direct W2 position with Bright Vision Technologies.
This role is part of Bright Vision Technologies’ in-house Statement of Work (SOW) engagement. The client, end customer, and employer for this position is Bright Vision Technologies — there is no third-party client, vendor, or implementation partner involved.
We do not engage in C2C, 1099, or third-party arrangements for this role.
BUT STRICTLY NO C2C/1099/3RD PARTY COMPANIES. ALL OUR ROLES ARE W2 AND NO 3RD PARTY BROKERING PLEASE.
Candidates must be willing to work directly as a full-time W2 employee of Bright Vision Technologies and contribute to our in-house SOW deliverables.
No new H1B sponsorship is available for this role.
However, candidates who are currently on a valid H1B visa and require a transfer are welcome to apply. We will support H1B transfers for qualified candidates.
For every role, a technical coding assessment is mandatory. Please apply only if you are confident in your technical abilities and hands-on experience.
Job Summary
We are looking for a Reinforcement Learning Engineer to design, train, and deploy RL-based systems for high-impact decision-making problems where supervised learning alone is insufficient. The role requires deep familiarity with modern reinforcement learning algorithms, simulation environments, reward modeling, and the engineering complexity of training and evaluating policies at scale. The ideal candidate has both research depth and engineering pragmatism, with experience taking RL solutions out of the lab and into production where stability, safety, and ongoing improvement are critical.
Key Responsibilities
  • Design and implement reinforcement learning solutions for sequential decision-making problems in real and simulated environments.
  • Develop, calibrate, and maintain simulation environments suitable for large-scale agent training.
  • Implement and evaluate modern RL algorithms including policy gradient, actor-critic, off-policy, and offline RL methods.
  • Engineer reward functions and shaping strategies that align agent behavior with desired outcomes and safety constraints.
  • Apply offline RL and imitation learning techniques where exploration is costly or unsafe.
  • Use RLHF, DPO, and related techniques for fine-tuning large language models when relevant.
  • Build scalable training infrastructure for distributed RL, including efficient experience collection and replay systems.
  • Optimize training stability and sample efficiency through algorithmic and engineering improvements.
  • Design rigorous evaluation protocols, including out-of-distribution and adversarial test cases.
  • Implement safety mechanisms such as constraint enforcement, conservative policies, and human-in-the-loop oversight.
  • Collaborate with applied scientists and product teams to identify high-value RL use cases.
  • Monitor deployed policies and models in production for drift, regression, and unintended behaviors, building the alerting and dashboards that surface issues before they meaningfully affect users.
  • Document methodology, design decisions, and operational characteristics for internal stakeholders.
  • Stay current with RL research and translate promising techniques into production-ready solutions.
Required Qualifications
  • Master’s or PhD in Computer Science, Machine Learning, or a related field; or equivalent applied experience.
  • Six or more years of combined RL research and engineering experience.
  • Strong proficiency in Python and modern deep learning frameworks.
  • Hands-on experience with at least one major RL library or in-house RL stack.
  • Solid understanding of probability, optimization, and the theoretical foundations of RL.
  • Experience designing and tuning reward functions in non-trivial environments.
  • Familiarity with simulation environments and large-scale experience collection.
  • Experience training neural network policies on GPU clusters.
  • Strong written and verbal communication skills.
  • Track record of shipping or publishing impactful RL work.
Preferred Qualifications
  • Experience with RLHF for large language models.
  • Familiarity with multi-agent RL or hierarchical RL.
  • Exposure to robotics, control systems, or autonomous driving.
  • Publications in RL or related research venues.
  • Open-source contributions to RL libraries or environments.
How to Apply
Would you like to know more about this opportunity?
For immediate consideration, please send your resume to venkat.r@bvteck.com or contact us at (908) 505-3899. Learn more about Bright Vision Technologies at www.bvteck.com.
We recognize that our people are our strength, and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company.
We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs.
Bright Vision Technologies is an Equal Opportunity Employer, including Disability/Veterans.
Position offered by “No Fee Agency.”
 

Equal Employment Opportunity (EEO) Statement

Bright Vision Technologies (BV Teck) is committed to equal employment opportunity (EEO) for all employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other protected status as defined by applicable federal, state, or local laws. This commitment extends to all aspects of employment, including recruitment, hiring, training, compensation, promotion, transfer, leaves of absence, termination, layoffs, and recall.

BV Teck expressly prohibits any form of workplace harassment or discrimination. Any improper interference with employees' ability to perform their job duties may result in disciplinary action up to and including termination of employment.