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Today

AI Engineer III – Computational Drug Discovery AI Model Development

Sam Quest Solutions Inc. Remote 🌍 Remote

Remote

Today

$70 - $100/hr Full time Ai Model Training Artificial Intelligence Computational Drug Discovery

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Job Description

Sam Quest Solutions Inc. is hiring an AI Engineer III to help build and refine AI/ML modeling capabilities for computational drug discovery. This role centers on developing, fine-tuning, and benchmarking models that move from protein/ligand sequence inputs to predictions of 3D structure and affinity, supporting multiple lead optimization programs.

In this remote position, you will design automated workflows and evaluate model performance across scientific datasets, with a focus on runtime efficiency and reproducible results. The work includes comparing alternative pose generation and docking approaches and determining how models should be structured for project-specific versus cross-project use.

What you’ll do

Fine-tune pre-trained foundation models such as Boltz-2 and AISB using domain-specific project data
Compile and curate datasets from multiple LO projects, including experimental protein-ligand complex structures and potency or affinity measurements
Analyze dataset variation to stress-test model applicability domains
Benchmark model performance against established methods including DeepAutoQSAR, GatorAffinity, MPNN, MM-GBSA, FEP, and related approaches
Compare co-folder pose generation against docking-based methods
Measure recall and precision using project-specific thresholds and build model ranking based on confidence and applicability domain
Assess whether a single fine-tuned co-folder model can serve multiple projects or whether project-specific models are required
Design an automated, end-to-end workflow optimized to produce single predictions in under a minute using GPU or CPU

What you bring

Strong experience in machine learning, computational chemistry, cheminformatics, or related scientific data science domains
Experience training and fine-tuning models on domain-specific scientific datasets
Experience with 3D modeling workflows, pose generation, or docking-based comparison studies
Working knowledge of benchmarking methodologies and model performance evaluation
Strong Python skills, including scripting and automation
Ability to build reproducible, scalable model workflows with runtime efficiency in mind
Collaboration and communication skills across scientific and technical teams

Technologies

Python
GPU, CPU
Boltz-2, AISB
DeepAutoQSAR, GatorAffinity
MPNN, MM-GBSA, FEP

Compensation and location

Location: Remote
Pay: USD 70 - 100 per hour

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1d ago

AI Engineer, Whole Body Controls, Optimus

Tesla Palo Alto, CA

Palo Alto, CA

1d ago

$176k - $420k/yr Full time Ai Model Training Artificial Intelligence Data Pipeline

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Job Description

Build whole-body motion policy models for Optimus on Tesla’s Whole Body Controls team, spanning training from pre-training through reinforcement learning.

Responsibilities

Design and iterate on network architectures for whole-body motion policies, world models, and learned dynamics models
Build, tune, and scale training recipes including losses, curricula, optimization, and pre-training to reinforcement-learning pipelines
Create robust data pipelines and data engines to feed model training at scale
Develop evaluation benchmarks that support fast, iterative model improvement
Increase the robustness of learned policies and deploy them on Optimus

Requirements

Proficiency in Python (including numpy and PyTorch)
Deep learning fundamentals covering architectures, optimization, training dynamics, and representation learning
Proficiency with modern network architectures (for example, transformers and sequence models), including experience designing and adapting them
Experience training neural networks in PyTorch, including large-scale or distributed training
Experience building robust data pipelines and data engines for large-scale model training
Preferred: experience designing novel architectures or training recipes that shipped to production; exposure to world models, imitation learning, or reinforcement learning; any robotics, control, or multimodal-sensing exposure
Equivalent experience through projects, research, or coursework is acceptable

Technologies

Python
numpy
pytorch / PyTorch
transformers
sequence models

Location

Palo Alto, CA (onsite)

Compensation

Expected compensation: $176,000 - $420,000 per year
May include cash and stock awards and benefits
Pay offered may vary based on individualized factors; total compensation package may include other elements depending on the position offered

Benefits

Medical plans with options including $0 payroll deduction, and healthcare at day 1 of hire
Family-building, fertility, adoption, and surrogacy benefits
Dental (including orthodontic coverage) and vision plans with options including a $0 paycheck contribution
Company paid HSA contribution when enrolled in the High-Deductible medical plan with HSA (Health Savings Accounts)
Healthcare and Dependent Care Flexible Spending Accounts (FSA)
401(k) with employer match
Employee Stock Purchase Plans
Other financial benefits
Company paid Basic Life, AD&D
Short-term and long-term disability insurance (90 day waiting period)
Employee Assistance Program
Sick and Vacation time (Flex time for salary positions, accrued hours for Hourly positions) and paid holidays
Back-up childcare and parenting support resources
Voluntary benefits: critical illness, hospital indemnity, accident insurance, theft & legal services, and pet insurance
Weight Loss and Tobacco Cessation Programs
Tesla Babies program
Commuter benefits
Employee discounts and perks program

Equal Opportunity & Accommodations

Tesla is an equal opportunity / affirmative action employer committed to diversity in the workplace
All qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, age, national origin, disability, protected veteran status, gender identity, or any other factor protected by applicable federal, state, or local laws
Tesla is committed to working with and providing reasonable accommodations to individuals with disabilities; let your recruiter know if you need an accommodation during the interview process

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5d ago

Machine Learning Engineer - AI Trainer

DataAnnotation Massachusetts 🇺🇸 Remote

Massachusetts

5d ago

$50 - $100/hr Contract Ai Ml Ai Model Training Ai Training

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Job Description

DataAnnotation is seeking an experienced Machine Learning Engineer - AI Trainer to evaluate and help train AI systems focused on quantitative reasoning. This is a remote contract opportunity based in Massachusetts, with flexible project selection and work timing after completing a short assessment.

Key Responsibilities

Review AI-generated quantitative work, including statistical analysis, predictive modeling, scientific reasoning, and data-driven insights, ensuring both technical accuracy and real-world validity.
Develop and solve quantitative problems used to train and benchmark AI systems, covering areas such as forecasting, experimental analysis, optimization, and statistical inference.
Produce clear technical explanations and well-documented analytical code.
Provide feedback that informs and improves the next generation of AI models built for quantitative reasoning.

Required Qualifications

2+ years of hands-on experience in a quantitative role or research environment, such as data science, statistics, economics, finance, physics, biology, epidemiology, operations research, or a closely related field.
Some coding experience with the ability to write and review analytical code end-to-end.
Practical experience with statistical methods, predictive modeling, and experiment design, including examples like A/B testing, hypothesis testing, regression, classification, and time-series forecasting.
English fluency at native or bilingual level, along with strong writing skills.
A bachelor’s degree in a quantitative field is preferred (Statistics, Computer Science, Mathematics, Engineering, or similar). A master’s or PhD is a plus.
Relevant credentials are a plus, such as Kaggle Competition ranking, AWS/GCP ML certifications, or equivalent demonstrated expertise.

Technologies

Kaggle
AWS
GCP

Compensation and Employment Details

Job type: Contract
Location: Massachusetts (remote)
Pay: USD 50–100 per hourly (projects are paid hourly, up to $60 USD per hour, with potential for higher-paying projects based on performance)
Experience level: Minimum 2 years

Remote Work and Availability

Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New Zealand.
Flexible schedule: choose which projects to take on and when you work.

Assessment Process

After you sign up for an account, you’ll complete a short assessment as a version of an interview. If you pass, you will receive an email confirmation and paid work will become available on the platform.

Additional Notes

Payment is made via PayPal.
DataAnnotation will never ask for any money from you.

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5d ago

Machine Learning Engineer - AI Trainer

DataAnnotation Washington, DC 🇺🇸 Remote

Washington, DC

5d ago

$50 - $100/hr Full time Ai Ml Ai Model Training Ai Trainer

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Job Description

Join DataAnnotation as a Machine Learning Engineer - AI Trainer to evaluate and help train AI systems focused on quantitative reasoning.

Responsibilities

Review AI-generated quantitative outputs, including statistical analysis, predictive modeling, scientific reasoning, and data-driven insights, for technical accuracy and real-world validity
Create and solve quantitative problems used to train and benchmark AI systems across forecasting, experimental analysis, optimization, and statistical inference
Produce clear technical explanations alongside well-documented analytical code
Deliver feedback that informs and improves the next generation of AI models for quantitative reasoning tasks

Requirements

2+ years of hands-on experience in a quantitative role or research environment (data science, statistics, economics, finance, physics, biology, epidemiology, operations research, or related)
Coding experience required, with comfort writing and reviewing analytical code end-to-end
Practical experience with statistical methods, predictive modeling, and experiment design, including examples such as A/B testing, hypothesis testing, regression, classification, and time-series forecasting
English fluency (native or bilingual level) with strong writing skills
Bachelor’s degree in a quantitative field preferred (Statistics, Computer Science, Mathematics, Engineering, or similar); master’s or PhD is a plus
Relevant credentials are a plus, such as Kaggle Competition ranking or AWS/GCP ML certifications (or equivalent demonstrated expertise)

Benefits

Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New Zealand
Flexible schedule: choose which projects to take on and when you work
Competitive pay: paid hourly; up to $60 USD per hour for strong performance (salary range listed: USD 50 - 100 per hourly)
Impact: help shape AI systems that reason about data and analytics

Additional Information

Payment method: PayPal
No money will be requested from applicants
This role is available only to candidates located in the US, Canada, UK, Ireland, Australia, and New Zealand

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9d ago

Data Scientist - AI Trainer

DataAnnotation Beaverton, OR 🇺🇸 Remote

Beaverton, OR

9d ago

$50 - $100/hr Contract Ai Model Training Ai Trainer Ai Training

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Job Description

Work fully remote and set your own pace. DataAnnotation is seeking an existing Data Scientist - AI Trainer to support AI training by assessing quantitative model outputs, building and solving benchmarking problems, and providing clear feedback that helps AI systems reason about data and scientific questions. This is a contract role with flexible scheduling and hourly pay of $50 to $100 USD, with bonus rates available on some projects. Payment is made via PayPal.

In this role, your work directly supports the next generation of AI tools designed for quantitative reasoning. You will evaluate technical outputs for accuracy and real-world validity, and help shape how models learn from data, experiments, and analytical tasks.

Responsibilities

Review and evaluate AI-generated quantitative work, including statistical analysis, predictive modeling, scientific reasoning, and data-driven insights, with a focus on technical accuracy and real-world validity.
Develop quantitative problems that are used to train and benchmark AI systems, covering topics such as forecasting, experimental analysis, optimization, and statistical inference.
Produce clear technical explanations and maintain well-documented analytical code.
Provide feedback that informs iterative updates to AI models built for quantitative reasoning and data analytics.

Requirements

3+ years of hands-on experience in a quantitative role or research environment (for example, data science, statistics, economics, finance, physics, biology, epidemiology, operations research, or a related field).
Some coding experience, with comfort writing and reviewing analytical code end-to-end.
Practical experience with statistical methods, predictive modeling, and experiment design (including A/B testing, hypothesis testing, regression, classification, and time-series forecasting).
Fluency in English (native or bilingual level) with strong writing skills.
A bachelor’s degree in a quantitative field is preferred (Statistics, Computer Science, Mathematics, Engineering, or similar); a Master’s or PhD is a plus.
Relevant credentials are a plus, such as Kaggle Competition ranking, AWS/GCP ML certifications, or equivalent demonstrated expertise.

Benefits

Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New Zealand.
Flexible schedule: choose which projects you take on and when you work, using your own computer from home.
Competitive pay: projects are paid hourly at $50 to $100 USD per hour, with bonus rates available on some projects.
Impact: contribute to AI systems that reason about data and analytics.

Important notes: Payment is made via PayPal. DataAnnotation will never ask for any money. This job is only available to candidates located in the US, Canada, UK, Ireland, Australia, and New Zealand.

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9d ago

Senior Data Scientist - AI Trainer

DataAnnotation Centennial, CO 🇺🇸 Remote

Centennial, CO

9d ago

$50 - $100/hr Contract Senior Ai Model Training Ai Trainer

Apply Now

Job Description

DataAnnotation is hiring a Senior Data Scientist - AI Trainer to evaluate and improve AI systems that perform quantitative reasoning.

Responsibilities

Assess AI-generated quantitative work, including statistical analysis, predictive modeling, scientific reasoning, and data-driven insights, focusing on technical correctness and real-world validity
Develop and solve quantitative problems used to train and benchmark AI systems
Cover problem areas such as forecasting, experimental analysis, optimization, and statistical inference
Produce clear technical explanations
Write well-documented analytical code and contribute to end-to-end analytical workflows
Deliver feedback that directly influences the next generation of AI models for quantitative reasoning

Requirements

3+ years of hands-on experience in a quantitative role or research environment (examples: data science, statistics, economics, finance, physics, biology, epidemiology, operations research, or adjacent fields)
Coding experience required, including comfort writing and reviewing analytical code end-to-end
Practical background with statistical methods, predictive modeling, and experiment design, including A/B testing and hypothesis testing
Experience with regression, classification, and time-series forecasting
English fluency (native or bilingual) with strong writing skills
Bachelor’s degree in a quantitative field preferred (Statistics, Computer Science, Mathematics, Engineering, or similar); Master’s or PhD is a plus
Relevant credentials are a plus, such as Kaggle Competition ranking, AWS/GCP ML certifications, or equivalent demonstrated expertise

Benefits

Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New Zealand
Flexible schedule: select projects and work timing; use your own computer from home
Competitive pay: projects paid hourly at $50 to $100 USD/hour, with bonus rates available on some projects
Impact: contribute to AI systems built to reason about data and analytics

Contracting with DataAnnotation

Fully remote across the US, Canada, UK, Ireland, Australia, and New Zealand
Flexible scheduling and project selection
Hourly compensation between $50 and $100 USD, with bonus rates on some projects
Opportunity to help shape AI systems for quantitative reasoning

Notes

Payment is made via PayPal
They will never ask for money from you
Role availability limited to candidates located in the US, Canada, UK, Ireland, Australia, or New Zealand

How to Get Started

After signing up for an account, complete a short assessment (their version of an interview)
If you pass, you receive an email confirmation
Paid work becomes available on their platform

View full job page →

9d ago

Senior Data Scientist - AI Trainer

DataAnnotation Minnesota 📍 United States Remote

Minnesota

9d ago

$50 - $100/hr Contract Senior Ai Model Training Ai Trainer

Apply Now

Job Description

The Senior Data Scientist - AI Trainer role supports the training and evaluation of AI models by reviewing quantitative outputs, creating rigorous quantitative tasks, and delivering technical feedback. This is a fully remote contract position with flexible scheduling and hourly compensation.

Role Summary

As an AI Trainer, you will assess AI-generated quantitative work for correctness and real-world validity, develop quantitative problems for training and benchmarking, and provide clear, actionable feedback. Work is paid hourly and performed remotely.

Responsibilities

Evaluate AI-generated quantitative work, including statistical analysis, predictive modeling, scientific reasoning, and data-driven insights, focusing on technical accuracy and real-world applicability.
Design and solve quantitative problems used to train and benchmark AI systems across areas such as forecasting, experimental analysis, optimization, and statistical inference.
Produce clear technical explanations and maintain well-documented analytical code.
Deliver feedback that informs iteration and improves the next generation of AI models focused on quantitative reasoning.

Requirements

3+ years of hands-on experience in a quantitative role or research environment, such as data science, statistics, economics, finance, physics, biology, epidemiology, operations research, or a closely related field.
Some coding experience, including the ability to write and review analytical code end-to-end.
Practical experience with statistical methods, predictive modeling, and experiment design, including examples such as A/B testing, hypothesis testing, regression, classification, and time-series forecasting.
Fluency in English (native or bilingual level) with strong writing skills.
A bachelor’s degree in a quantitative field is preferred (Statistics, Computer Science, Mathematics, Engineering, or similar). A Master’s or PhD is a plus.
Relevant credentials are a plus, such as Kaggle Competition ranking, AWS/GCP ML certifications, or equivalent demonstrated expertise.

Technologies

English
Kaggle
AWS
GCP

Compensation and Work Model

Job type: Contract
Location: Remote (Wyoming)
Pay: USD 50 to 100 per hour

Benefits

Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New Zealand.
Flexible schedule: select which projects to take on and when to work, using your own computer.
Competitive pay: hourly projects at $50 to $100 USD per hour, with bonus rates available on some projects.
Impact: contribute to AI systems designed to reason about data and analytics.

Additional Notes

Payment is made via PayPal.
No money is requested from candidates.
This role is available only to residents of the US, Canada, UK, Ireland, Australia, and New Zealand.

View full job page →

Ai Model Training Data Jobs

AI Engineer III – Computational Drug Discovery AI Model Development

AI Engineer, Whole Body Controls, Optimus

Machine Learning Engineer - AI Trainer

Machine Learning Engineer - AI Trainer

Data Scientist - AI Trainer

Senior Data Scientist - AI Trainer

Senior Data Scientist - AI Trainer

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