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Commission Rlhf Jobs in Massachusetts (NOW HIRING)

Applied AI Scientist - Hybrid

Boston, MA · On-site

$100K - $120K/yr

Practical experience applying reinforcement learning (e.g., RLHF, or RL for agent behavior and ... This is an incentive-based position, which may include bonuses, incentive or commission plans.

Practical experience applying reinforcement learning (e.g., RLHF, or RL for agent behavior and ... This is an incentive-based position, which may include bonuses, incentive or commission plans.

Practical experience applying reinforcement learning (e.g., RLHF, or RL for agent behavior and ... This is an incentive-based position, which may include bonuses, incentive or commission plans.

Commission Rlhf information

What is a Commission RLHF?

Commission RLHF jobs typically involve working on Reinforcement Learning from Human Feedback (RLHF) projects in a commission-based role. RLHF is an approach in artificial intelligence where models are trained using feedback from humans to improve their performance and alignment with human values. People in these jobs might collect and analyze human feedback, design reward models, or fine-tune AI systems. The commission aspect usually means pay is based on deliverables or performance rather than a fixed salary. These roles require strong analytical and communication skills, as well as some familiarity with machine learning concepts.

What are the key skills and qualifications needed to thrive as a Commission RLHF specialist?

To thrive as a Commission RLHF (Reinforcement Learning from Human Feedback) Specialist, you need a strong background in machine learning, data analysis, and computer science, often supported by an advanced degree in a related field. Familiarity with frameworks like PyTorch or TensorFlow, experience in NLP models, and understanding of annotation tools are typically required. Strong analytical thinking, attention to detail, and effective communication skills help you interpret human feedback and collaborate with cross-functional teams. These skills are essential for developing and refining AI systems that accurately learn from and adapt to human input.

How do Commission RLHF professionals typically collaborate with cross-functional teams to implement reinforcement learning from human feedback in production environments?

Commission RLHF professionals frequently work alongside data scientists, machine learning engineers, and product managers to integrate reinforcement learning from human feedback (RLHF) into real-world applications. Collaboration often involves aligning on data collection strategies, interpreting human feedback, and iterating on model performance. Effective communication and coordination are crucial, as RLHF requires a blend of technical expertise and an understanding of user intent. Regular team meetings and joint problem-solving sessions help ensure that the RLHF models meet both technical and business objectives.

What is the difference between Commission Rlhf vs Real Estate Agent?

AspectCommission RlhfReal Estate Agent
CredentialsReal estate license, RLIHF certificationReal estate license
Work EnvironmentReal estate agencies, brokerage firmsReal estate agencies, brokerage firms
Industry UsageReal estate transactions, property salesProperty sales, leasing, market analysis
Search/Comparison IntentUnderstanding roles, certifications, and dutiesCareer info, licensing, job responsibilities

Commission Rlhf professionals focus on real estate transactions with specific certifications, while real estate agents perform similar duties but may not hold the RLIHF credential. Both work in real estate agencies and assist clients in buying, selling, or leasing properties. The main difference lies in the certification and possibly scope of practice, making it important for clients and job seekers to understand these distinctions.

What are the most commonly searched types of Rlhf jobs in Massachusetts?

The most popular types of Rlhf jobs in Massachusetts are:

What job categories do people searching Commission Rlhf jobs in Massachusetts look for?

The top searched job categories for Commission Rlhf jobs in Massachusetts are:

What cities in Massachusetts are hiring for Commission Rlhf jobs?

Cities in Massachusetts with the most Commission Rlhf job openings:

Infographic showing various Commission Rlhf job openings in Massachusetts as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 8% Part Time, and 6% Contract. Highlights an 67% Physical, 1% Hybrid, and 32% Remote job distribution.

Applied AI Scientist - Hybrid

Boston, MA • On-site


XPO Logistics
Import-Export • 10K+ employees

6.9

Company rating: 6.9 out of 10

Based on 224 frontline employees who took The Breakroom Quiz

231st of 366 rated logistics

Recommended by students

Respectful managers

Uninterrupted breaks


$100K - $120K/yr

Full-time

Medical, Life, Retirement, PTO

Posted 9 days ago


Job description

Please note that the following enhanced screening and interview requirements apply to this role: Virtual backgrounds or headphones / earbuds are not permitted during web-based interviews. Additionally, a minimum of one onsite, in person interview will be required as part of the application process. By choosing to apply, you acknowledge and agree to these requirements.
What you'll need to succeed as an Applied AI Scientist at XPO:
Minimum qualifications:
  • Bachelor's degree or equivalent related work or military experience
  • 1 year of experience designing evaluation harnesses or benchmarks to rigorously assess model or agent performance against existing baselines
  • Hands-on experience building applied AI systems, including one or more of: agent-based/agentic systems, experimentation frameworks, or applying LLM-based/foundation model architectures to time-series forecasting problems
  • Proficiency in Python and modern ML/AI frameworks and platforms (e.g. PyTorch, HuggingFace)
  • Strong communication skills, with the ability to explain AI system behavior and tradeoffs to technical and business stakeholders, and to collaborate closely with optimization/OR scientists on what constitutes a meaningful model improvement

Preferred qualifications:
  • Bachelor's degree in Computer Science, AI, Data Science, Engineering, or related field, or equivalent related work or military experience
  • Master's degree or PhD in Computer Science, AI, Machine Learning, Statistics, or related field
  • 2+ years of experience building agentic systems for production use cases and/or R&D applications
  • Experience designing operational safeguards (e.g., automated checks against regressions, runaway compute, or unvalidated models reaching production) for agent-based systems
  • Practical experience applying time-series or tabular foundation models (e.g., Chronos or similar) to forecasting problems such as ETA prediction or demand forecasting
  • Practical experience with foundation model fine-tuning or post-training techniques
  • Practical experience applying reinforcement learning (e.g., RLHF, or RL for agent behavior and decision-making)
  • Experience building retrieval-augmented generation (RAG) systems is a plus
  • Experience applying agentic or applied AI techniques to logistics, transportation, or operations research domains

About the Applied AI Scientist job:
Pay, Benefits and more:
  • Competitive compensation package
  • Full health insurance benefits available on day one
  • Life and disability insurance
  • Earn up to 15 days of PTO over your first year
  • 9 paid company holidays
  • 401(k) option with company match
  • Education assistance
  • Opportunity to participate in a company incentive plan

What you'll do on a typical day:
  • Design and build agentic experimentation layer over optimization models developed by the team's OR/data scientists, including proposing variants, running evaluations, and surfacing promising results
  • Build evaluation harnesses that rigorously and automatically benchmark model and agent performance against existing baselines before promotion to production
  • Implement operational safeguards for autonomous experimentation systems, such as automated regression checks, compute/cost limits, and human-in-the-loop gates before production promotion
  • Evaluate and integrate modern LLM-based and foundation model architectures (e.g., Chronos-style time-series models) for ETA prediction and demand forecasting for pickup prediction
  • Partner closely with the team's optimization/OR scientists to understand model internals, solver behavior, and what constitutes a meaningful improvement for P&D use cases
  • Partner with machine learning engineers on the underlying infrastructure needed to run automated experimentation and evaluation at scale
  • Communicate technical approaches and tradeoffs to both technical and business audiences
  • Stay current on advances in agentic systems, time-series foundation models, and applied GenAI to guide adoption at XPO

Annual Salary Range: $100,000 to $120,000 Actual compensation may vary due to factors such as experience and skill set. This is an incentive-based position, which may include bonuses, incentive or commission plans.
About XPO
XPO is a top ten global provider of transportation services, with a highly integrated network of people, technology and physical assets. At XPO, we look for employees who like a challenge and can communicate effectively in all situations. We want to leverage your skills and years of experience to drive positive results while ensuring a bright future for yourself and XPO. If you're looking for a growth opportunity, join us at XPO.
We are proud to be an Equal Opportunity employer. Qualified applicants will receive consideration for employment without regard to race, sex, disability, veteran or other protected status.
All applicants who receive a conditional offer of employment may be required to take and pass a pre-employment drug test.
The above statements are not an exhaustive list of all required responsibilities, duties and skills for this job classification.
Review XPO's candidate privacy statement here.

XPO logo

About XPO

Sourced by ZipRecruiter

Founded in Greenwich, Connecticut, XPO Logistics, Inc., operating under the brand name XPO, is a one of the leading companies in the transportation and logistics sector. Operating its services in 30 countries, the company employs the use of ground-breaking technology in providing a broad suite of logistics services including supply chain management, freight brokerage, last mile logistics, and intermodal and drayage transportation. XPO's impressive history dates back to 2011 and within its relatively short existence, it has made a series of acquisitions to consolidate its top-notch range of services. Their mission is to provide outstanding results to customers by envisioning and implementing significant advancements in freight transportation and logistics.

Industry

Import-export

Company size

10,000+ Employees

Headquarters location

Greenwich, CT, US


What XPO employees say

Pay

Benefits

Hours and flexibility

Workplace

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