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ai computational data scientist

MD Anderson Cancer Center

<div>We seek a talented, energetic, and collaborative AI-driven Data Scientist to develop data science tools and predictive algorithms as part of the development of our flagship platform A3D3a: Adaptive, AI-augmented, Drug Discovery and Development. With expertise in Machine Learning and Deep Learning, the Data Scientist will inform our mission to discover novel therapeutic opportunities for cancer patients. 
 
Led by Prof. Bissan Al-Lazikani, Director of Therapeutics Data Science, the intelligent and ever-learning A3D3a platform is part of MD Anderson's Therapeutics Data Science initiative and part of our ambitious Institute for Data Science in Oncology. A3D3a will accelerate the discovery and impact of novel therapies for cancer by enabling novel opportunities for optimized therapies for patients with a focus on rare and hard-to-treat cancers through the development of novel machine learning and AI technologies. 
 
Central to this vision, the Data Scientist will innovate and deploy Machine Learning and Deep Learning approaches to uncover hidden therapeutic opportunities in integrated patient data and will work closely with biologists, data scientists, and clinicians. 
 
The ideal candidate has strong hands-on experience with machine learning, deep learning, and large language models, and is comfortable using tools like TensorFlow, Keras, and scikit-learn. They can address challenges such as data bias and imbalance, have solid programming skills in Python or similar languages, and possess a strong understanding of statistical methods. This person enjoys solving complex problems and developing practical AI solutions that make a meaningful impact.
 
 
What We Offer? 
<ul><li>Employer-paid medical coverage starting day one for employees working 30+ hours/week, plus optional group dental, vision, life, AD&amp;D, and disability insurance.</li><li>Accruals for PTO and Extended Illness Bank, plus paid holidays, wellness, childcare, and other leave options.</li><li>Tuition Assistance Program after six months of service and access to extensive wellness, fitness, and employee resource groups.</li><li>Defined-benefit pension through the Teachers Retirement System, voluntary retirement plans, and employer-paid life and reduced salary protection programs.</li></ul> 

JOB RESPONSIBILITIES: 
<ul><li>Build data science tools and predictive algorithms focusing on state-of-art machine learning models</li><li>Develop novel deep learning approaches and utilizing Large Language Models and Graph Neural Networks for cancer data</li><li>Maintain knowledge of cutting-edge machine learning approaches and technologies and implement these where appropriate</li><li>Perform data wrangling and preparation for deep learning analysis</li><li>Perform statistical analysis</li><li>Produce output for scientific publications and co-author said publications</li><li>Prepare written reports, manuscripts, and grant applications with investigators</li><li>Attend collaborator meetings and team working group meetings. Prioritize and manage multiple projects in a timely and resource-effective manner.</li><li>Stay up to date with relevant literature, gather information systematically, and confer with the supervisor regarding new procedures.</li><li>Other Duties as assigned.</li></ul> 

EXPECTED SKILLS:
 
<ul><li>Machine Learning (e.g., Na&iuml;ve Bayes, Random Forests, Support Vector Machines, etc.)</li><li>Deep Learning (e.g., Convolutional Neural Networks, Graph Neural Networks, Autoencoders, etc.)</li><li>LLM (fine-tuning, multi-agents)</li><li>Addressing challenges in Machine Learning / Deep Learning as well as mitigation strategies including data bias, imbalance, and model validation approaches</li><li>Machine-learning platforms (e.g., TensorFlow, sklearn, Keras, etc.)</li><li>Unix, Python, R/Matlab, or other scripting/programming languages</li><li>Excellent working knowledge of statistical methods and tests</li></ul> 

EDUCATION: 
Required: Bachelor's Degree Biomedical Engineering, Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Science, Engineering, Computer Science, Statistics, Computational Biology, or related field. 
Preferred: Master's or PhD in Science, Engineering or related field. 
 
EXPERIENCE: 
Required: Three years scientific software or industry development/analysis experience. With Master's degree one year. With PhD, no experience required. 
Preferred: Machine Learning, Large language model, AI Agent and/or Biomedical Research is a plus.
 
 
The University of Texas MD Anderson Cancer Center offers excellent benefits, including medical, dental, paid time off, retirement, tuition benefits, educational opportunities, and individual and team recognition. 
 
This position may be responsible for maintaining the security and integrity of critical infrastructure, as defined in Section 113.001(2) of the Texas Business and Commerce Code and therefore may require routine reviews and screening. The ability to satisfy and maintain all requirements necessary to ensure the continued security and integrity of such infrastructure is a condition of hire and continued employment. 
 
It is the policy of The University of Texas MD Anderson Cancer Center to provide equal employment opportunity without regard to race, color, religion, age, national origin, sex, gender, sexual orientation, gender identity/expression, disability, protected veteran status, genetic information, or any other basis protected by institutional policy or by federal, state, or local laws unless such distinction is required by law.http://www.mdanderson.org/about-us/legal-and-policy/legal-statements/eeo-affirmative-action.html 
 
Additional Information
 
<ul><li>Requisition ID: 179340
</li><li>Employment Status: Full-Time
</li><li>Employee Status: Regular
</li><li>Work Week: Days
</li><li>Minimum Salary: US Dollar (USD) 106,500
</li><li>Midpoint Salary: US Dollar (USD) 133,000
</li><li>Maximum Salary : US Dollar (USD) 159,500
</li><li>FLSA: exempt and not eligible for overtime pay
</li><li>Fund Type: Soft
</li><li>Work Location: Hybrid Onsite/Remote
</li><li>Pivotal Position: Yes
</li><li>Referral Bonus Available?: Yes
</li><li>Relocation Assistance Available?: Yes
</li></ul> 
#LI-Hybrid</div>

AI Computational Data Scientist

<div>We seek a talented, energetic, and collaborative Molecular Modeling Scientist to conduct both routine and novel analyses as part of our flagship platform A3D3a: Adaptive, AI-augmented, Drug Discovery and Development. With experience in structural prediction, comparative modeling, and emerging generative models, the Molecular Modeling Scientist will contribute to the discovery of novel cancer therapeutics as part of A3D3a. 
 
Led by Prof. Bissan Al-Lazikani, Director of Therapeutics Data Science, the intelligent and ever-learning A3D3a platform is part of MD Anderson's Therapeutics Data Science initiative and part of our ambitious Institute for Data Science in Oncology. A3D3a will accelerate the discovery and impact of novel therapies for cancer by enabling novel opportunities for optimized therapies for patients with a focus on rare and hard-to-treat cancers through the development of novel machine learning and AI technologies. 
 
Central to this vision, the Molecular Modeling Scientist will leverage state-of-the-art macromolecular modeling techniques and, collaboratively with senior scientists, develop innovative data science approaches to answer structural questions about and nominate therapeutic targets. Additionally, physics-based modeling may also compliment structural informatics and generative AI efforts. The preferred candidate should have at least an MSc in Chemistry, Biochemistry, Computer Science, or a related field. A strong background in computational modeling and a willingness to learn new approaches is critical to this role. 
 
The ideal candidate will be an experienced computational scientist with strong Python-based scientific computing skills and expertise in cheminformatics, generative AI, and molecular modeling-capable of building predictive ML models, generating and analyzing macromolecular structures, leveraging tools such as PyTorch, Modeller, Rosetta, and MD packages, and contributing effectively to multidisciplinary research through rigorous documentation, scientific communication, and efficient project management.
 
 
JOB RESPONSIBILITIES:
 
<ul><li>Generate comparative macromolecular models of potential therapeutic targets</li><li>Build and apply machine/deep learning models to predict structural properties</li><li>Analyze ensembles of structures through techniques such as clustering</li><li>Document work thoroughly</li><li>Produce output for scientific publications and contribute to said publications</li><li>Present results at multidisciplinary project meetings as well as external meetings</li><li>Attend collaborator meetings and team working group meetings. Prioritize and manage multiple projects in a timely and resource-effective manner.</li><li>Stay up to date with relevant literature, gather information systematically, and confer with the supervisor regarding new procedures.
</li><li>Expertise in scientific computing using Python in a Unix environment</li><li>Proficient with generative AI for structure prediction; familiar with PyTorch.</li><li>Proficiency with Modeller, Rosetta, or other classical comparative modeling tools</li><li>Experience with OpenMM, AMBER, or comparable MD tools</li><li>Experience with molecular visualization tools (i.e., PyMol, VMD)</li><li>Familiar with basic statistical testing</li></ul> 
Other duties as assigned. 
 
EDUCATION:
 
Required: Bachelor's Degree Biomedical Engineering, Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Science, Engineering, Computer Science, Statistics, Computational Biology, or related field. 
Preferred: Master's or PhD Degree Science, Engineering or related field. 
 
EXPERIENCE: 
Required: Three years scientific software or industry development/analysis experience. With Master's degree, one year. With PhD, no experience required. 
Preferred: Proficent with PyTorch. Profient with comparative modeling tools. 
 
The University of Texas MD Anderson Cancer Center offers excellent benefits, including medical, dental, paid time off, retirement, tuition benefits, educational opportunities, and individual and team recognition. 
 
This position may be responsible for maintaining the security and integrity of critical infrastructure, as defined in Section 113.001(2) of the Texas Business and Commerce Code and therefore may require routine reviews and screening. The ability to satisfy and maintain all requirements necessary to ensure the continued security and integrity of such infrastructure is a condition of hire and continued employment. 
 
It is the policy of The University of Texas MD Anderson Cancer Center to provide equal employment opportunity without regard to race, color, religion, age, national origin, sex, gender, sexual orientation, gender identity/expression, disability, protected veteran status, genetic information, or any other basis protected by institutional policy or by federal, state, or local laws unless such distinction is required by law.http://www.mdanderson.org/about-us/legal-and-policy/legal-statements/eeo-affirmative-action.html 
 
Additional Information
 
<ul><li>Requisition ID: 179242
</li><li>Employment Status: Full-Time
</li><li>Employee Status: Regular
</li><li>Work Week: Days
</li><li>Minimum Salary: US Dollar (USD) 106,500
</li><li>Midpoint Salary: US Dollar (USD) 133,000
</li><li>Maximum Salary : US Dollar (USD) 159,500
</li><li>FLSA: exempt and not eligible for overtime pay
</li><li>Fund Type: Soft
</li><li>Work Location: Hybrid Onsite/Remote
</li><li>Pivotal Position: Yes
</li><li>Referral Bonus Available?: Yes
</li><li>Relocation Assistance Available?: Yes
</li></ul> 
#LI-Hybrid</div>

Data Scientist Molecular Modeling

YO IT Consulting

<div>
 Contract
 
 
 Remote
 
 
 Role Description
 
 
 As a remote, hourly paid R Engineer, you will review AI-generated responses and generate high-quality R and data-analysis-focused content, evaluating the reasoning quality and step-by-step problem-solving behind each solution. You will assess solutions for accuracy, clarity, and adherence to the prompt; identify errors in statistical methodology or data-wrangling workflows; fact-check analytical results; write expert-level explanations and model solutions that demonstrate correct use of R; and rate and compare multiple AI responses based on correctness and reasoning quality. This contract role is with, a fast-growing AI Data Services company and subsidiary of that provides AI training data for many of the world&rsquo;s largest AI companies and foundation model labs, directly helping to improve the world&rsquo;s premier AI models.
 
 
 Your Profile
 
 
 <ul>
 <li>
 2+ years of hands-on experience using R for data analysis, statistics, or data science work.
 </li>
 <li>
 Strong proficiency in R programming, including data wrangling, functional programming patterns, and writing reusable functions or packages.
 </li>
 <li>
 Solid grounding in applied statistics, including regression, inference, and model validation, with practical experience implementing these methods in R.
 </li>
 <li>
 Experience building end-to-end analyses in R that include data cleaning, exploratory analysis, modeling, and visualization.
 </li>
 <li>
 Familiarity with common R ecosystems such as tidyverse, data.table, and ggplot2, and the ability to choose appropriate tools for a given task.
 </li>
 <li>
 Professional experience in a data-focused role such as data scientist, statistician, quantitative analyst, or similar.
 </li>
 <li>
 Minimum Bachelor&rsquo;s degree in Statistics, Mathematics, Computer Science, or a closely related quantitative field.
 </li>
 <li>
 Significant experience using large language models (LLMs) to assist with coding, analysis design, and code review in R.
 </li>
 <li>
 Excellent English writing skills with the ability to document analyses and explain complex statistical ideas clearly to non-experts.
 </li>
 <li>
 Previous experience with AI data training or model evaluation is strongly preferred, and Minimum C1 English proficiency is required.
 
 
 </li>
 </ul>
 Key Responsibilities
 
 
 <ul>
 <li>
 Develop AI Training Content: Create detailed prompts in various topics and responses to guide AI learning, ensuring the models reflect a comprehensive understanding of diverse subjects.
 </li>
 <li>
 Optimize AI Performance: Evaluate and rank AI responses to enhance the model's accuracy, fluency, and contextual relevance.
 </li>
 <li>
 Ensure Model Integrity: Test AI models for potential inaccuracies or biases, validating their reliability across use cases.
 </li>
 </ul>
</div>

R - Programming Software Engineer

Andiamo

<div>
 Senior Machine Learning Scientist, Foundation Models for Time Series and Sensors
 
 
 We are looking for a Machine Learning Scientist who is excited by the challenge of teaching machines to understand the physical world through data. This role focuses on building large scale foundation models that learn deep representations from time series, sequential sensor streams, and other complex signals, with direct application to industrial, scientific, and real world systems.
 
 
 
 About The Role
 
 
 
 In this position, you will design, train, and deploy self supervised and semi supervised learning systems that operate across time series, sensor data, vision, and text. Your work will enable advanced capabilities such as anomaly and event detection, predictive maintenance, forecasting, classification, and sensor fusion. You will help define the next generation of intelligent systems that operate reliably in noisy, high consequence environments.
 
 
 What You Will Work On
 
 
 <ul>
 <li>
 Develop large scale foundation models that learn transferable representations from sequential and sensor based data
 </li>
 <li>
 Apply self supervised learning techniques to unlock value from unlabeled and weakly labeled datasets
 </li>
 <li>
 Fine tune and adapt pretrained models for specialized downstream tasks across industrial and scientific domains
 </li>
 <li>
 Design systems that combine time series, images, audio, text, and structured data into unified learning architectures
 </li>
 <li>
 Collaborate with domain experts to ensure models align with real world constraints and objectives
 
 
 </li>
 </ul>
 Data and Signal Processing Expertise
 
 
 <ul>
 <li>
 Process and analyze univariate and multivariate time series from domains such as industrial systems, IoT, finance, healthcare, or scientific instrumentation
 </li>
 <li>
 Perform data augmentation, feature extraction, resampling, and noise handling for real world sensor streams
 </li>
 <li>
 Work with diverse sensor modalities including vibration, temperature, accelerometers, audio, imagery, and more
 </li>
 <li>
 Handle synchronization challenges, variable sampling rates, and imperfect data collected in operational environments
 
 
 </li>
 </ul>
 Machine Learning and Model Development
 
 
 <ul>
 <li>
 Build models using sequence focused architectures such as recurrent networks, temporal convolutional networks, and transformer based systems
 </li>
 <li>
 Apply contrastive learning, masked prediction, temporal forecasting objectives, and multimodal alignment techniques
 </li>
 <li>
 Leverage transfer learning, adapter based methods, and few shot strategies for efficient adaptation
 </li>
 <li>
 Evaluate models using both technical metrics and end user or business driven performance indicators
 
 
 </li>
 </ul>
 Software and Training Infrastructure
 
 
 <ul>
 <li>
 Develop high performance pipelines in Python using scientific and data libraries
 </li>
 <li>
 Optimize components with C++ or CUDA when needed for large scale preprocessing or training
 </li>
 <li>
 Train models using modern deep learning frameworks such as PyTorch, TensorFlow, or JAX
 </li>
 <li>
 Scale training across multiple GPUs and nodes using distributed and mixed precision techniques
 </li>
 <li>
 Build reliable data pipelines for ingesting, cleaning, segmenting, and aligning massive sensor datasets
 
 
 </li>
 </ul>
 Mathematical and Algorithmic Foundations
 
 
 <ul>
 <li>
 Strong grounding in linear algebra, probability, statistics, and optimization
 </li>
 <li>
 Experience with signal processing methods such as Fourier analysis, wavelets, filtering, and time frequency techniques
 </li>
 <li>
 Familiarity with numerical methods for modeling dynamic systems and solving inverse problems
 
 
 </li>
 </ul>
 Collaboration and Communication
 
 
 <ul>
 <li>
 Work closely with engineers, researchers, product leaders, and end users from technical and non technical backgrounds
 </li>
 <li>
 Clearly explain model behavior, uncertainty, and tradeoffs to diverse audiences
 </li>
 <li>
 Contribute to documentation, design discussions, and technical decision making
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 MS or PhD in Computer Science, Artificial Intelligence, Data Science, or a closely related field
 </li>
 <li>
 Three or more years of hands on experience in machine learning, data science, or applied AI
 
 
 </li>
 </ul>
 This role offers the opportunity to work at the frontier of foundation models for time series and sensor data, solving problems that matter in the physical world and shaping systems that operate at scale in complex, real environments.
 
 
 
 About Andiamo
 
 
 
 Talent Partners for the AI Revolution. As a globally recognized staffing and consulting firm, we specialize in placing the top 2% of technology and go-to-market professionals with the world&rsquo;s largest and most well-known companies.
 
 
 For over 20 years, we've maintained the status of tier-one vendor for firms such as Palantir, Amazon, Fluidstack, Bloomberg, Relativity Space, Firefly, MasterCard, Visa, Two Sigma, Citadel, as well as other major financial services firms, elite hedge funds, Google-backed tech start-ups, and major software firms.
 
 
 Our talent solutions include Permanent Placement, Contract Staffing, Executive Search, and Dedicated Recruiting Services (RPO). Find out more at www.andiamogo.com
</div>

Data Scientist - Drilling - Global Energy Tech Company

The Jupiter Group, Inc

<div>
 
 &bull; This role is for a Data Scientist in the Supply Chain &amp; Manufacturing domain, with specific experience in areas like retail supply chain, inventory planning, and forecasting. The team is focused on predictive analytics and machine analytics, building real forecasting and ML models rather than just operating existing tools. GenAI and LLMs are being explored, but they are not mature yet and not the main focus of the role today.
 
 
 &bull; The team is currently working with KumoAI (recommendation software). They are building systems around inventory forecasting and vendor recommendation, and want to take those solutions further. Inventory planning is a key business problem they&rsquo;ve already solved once and are now enhancing with more advanced ML and deep learning approaches.
 
 
 &bull; They are looking for someone who has hands-on experience building different types of forecasting models and machine learning models in Python, not someone who only consumes models or uses black-box solutions. The expectation is that this person has designed their own models from scratch and productionized them using platforms like AWS and Databricks. They&rsquo;ve even built internal software for forecasting that the business can directly use.
 
 
 &bull; From a technical perspective, they want strong experience in deep learning for time series forecasting, especially for inventory forecasting and planning. There is very little NLP involved, so this is not an NLP-heavy role. The profile leans more toward a Full Stack Data Engineer / Data Scientist hybrid &mdash; someone who understands data pipelines, modeling, and deployment end-to-end.
 
 
 &bull; They specifically do not want black-box model users. They need someone who understands what is happening inside the models, can tune and improve them, and apply them directly to real business problems.
 
 
 
</div>

Data Scientist

Quest Diagnostics

<div>Medical Laboratory Scientist I - Houston, TX, Monday to Friday, 5:00 AM to 1:30 PM

Are you intrigued by the science of the human body? Curious about state-of-the-art laboratory instrumentation? Looking to join a Fortune 500 company leading the world in providing diagnostic information services? Quest Diagnostics is now recruiting for technologist positions ranging from entry level to experienced, with a wide range of benefits and training! 


Pay range: $29.50+ per hour

Salary offers are based on a wide range of factors including relevant skills, training, experience, education, and, where applicable, certifications obtained. Market and organizational factors are also considered. Successful candidates may be eligible to receive annual performance bonus compensation. 


Benefits information: 
We are proud to offer best-in-class benefits and programs to support employees and their families in living healthy, happy lives. Our pay and benefit plans have been designed to promote employee health in all respects &ndash; physical, financial, and developmental. Depending on whether it is a part-time or full-time position, some of the benefits offered may include:
<ul>
<li>Day 1 Medical, supplemental health, dental &amp; vision for FT employees who work 30+ hours</li>
<li>Best-in-class well-being programs</li>
<li>Annual, no-cost health assessment program Blueprint for Wellness&reg;</li>
<li>healthyMINDS mental health program</li>
<li>Vacation and Health/Flex Time</li>
<li>6 Holidays plus 1 &quot;MyDay&quot; off</li>
<li>FinFit financial coaching and services</li>
<li>401(k) pre-tax and/or Roth IRA with company match up to 5% after 12 months of service</li>
<li>Employee stock purchase plan</li>
<li>Life and disability insurance, plus buy-up option</li>
<li>Flexible Spending Accounts</li>
<li>Annual incentive plans</li>
<li>Matching gifts program</li>
<li>Education assistance through MyQuest for Education</li>
<li>Career advancement opportunities</li>
<li>and so much more!</li>
</ul><div><div><div><div>Quest Diagnostics honors our service members and encourages veterans to apply. 
 
While we appreciate and value our staffing partners, we do not accept unsolicited resumes from agencies. Quest will not be responsible for paying agency fees for any individual as to whom an agency has sent an unsolicited resume. 
 
Equal Opportunity Employer: Race/Color/Sex/Sexual Orientation/Gender Identity/Religion/National Origin/Disability/Vets or any other legally protected status.</div>
</div> 
</div></div>Job Responsibilities: 

<ul>
<li>Follow the laboratory's procedures for specimen handling and processing, test analyses, reporting and maintaining records of patient test result.</li>
<li>Maintain records that demonstrate that proficiency testing samples are tested in the same manner as patient specimens.</li>
<li>Analyze specimens using approved testing procedures.</li>
<li>Review and release test results.</li>
<li>Follow CLIA, HIPAA, OSHA, and safety guidelines as described in their respective guidelines.</li>
<li>Follow the laboratory's established policies and procedures whenever test systems are not within the laboratory's established acceptable levels of performance.</li>
<li>Identify problems that may adversely affect test performance or reporting of test results, correct the problems encountered or immediately notify the senior technologist or supervisor.</li>
</ul>
Education: 
BS in Medical Technology preferred; or BS/BA in Chemistry or Biology, or Associates degree in a Laboratory Science or Medical Technology, or Previously qualified as a Technologist under 42 CFR 493 


Work Experience: 
1 year Clinical experience (high complexity testing) preferred. 


MLS, Medical Laboratory Scientist, Medical Lab Scientist, Med Tech, Medical Technologist, CLS, Clinical Lab Scientist</div>

Medical Laboratory Scientist I

<div>
 
 Work Mode:
 
 Remote
 
 
 
 Engagement Type:
 
 Independent Contractor
 
 
 
 Schedule:
 
 Full-Time or Part-Time Contract
 
 
 
 Language Requirement:
 
 Fluent English
 
 
 
 Role Overview
 
 
 
 We partner with leading AI teams to improve the quality, usefulness, and reliability of general-purpose conversational AI systems.
 
 
 This project focuses specifically on evaluating and improving how AI systems reason about code, generate programming solutions, and explain technical concepts across various complexity levels.
 
 
 The role involves rigorous technical evaluation of AI-generated responses in coding and software engineering contexts.
 
 
 
 What You&rsquo;ll Do
 
 
 
 Evaluate LLM-generated responses to coding and software engineering queries for accuracy, reasoning, clarity, and completeness
 
 
 Conduct fact-checking using trusted public sources and authoritative references
 
 
 Conduct accuracy testing by executing code and validating outputs using appropriate tools
 
 
 Annotate model responses by identifying strengths, areas of improvement, and factual or conceptual inaccuracies
 
 
 Assess code quality, readability, algorithmic soundness, and explanation quality
 
 
 Ensure model responses align with expected conversational behavior and system guidelines
 
 
 Apply consistent evaluation standards by following clear taxonomies, benchmarks, and detailed evaluation guidelines
 
 
 
 Who You Are
 
 
 
 You hold a BS, MS, or PhD in Computer Science or a closely related field
 
 
 You have significant real-world experience in software engineering or related technical roles
 
 
 You are an expert in at least one relevant programming language (e.g., Python, Java, C++, JavaScript, Go, Rust)
 
 
 You are able to solve HackerRank or LeetCode Medium and Hard-level problems independently
 
 
 You have experience contributing to well-known open-source projects, including merged pull requests
 
 
 You have significant experience using LLMs while coding and understand their strengths and failure modes
 
 
 You have strong attention to detail and are comfortable evaluating complex technical reasoning, identifying subtle bugs or logical flaws
 
 
 
 Nice-to-Have Specialties
 
 
 
 Prior experience with RLHF, model evaluation, or data annotation work
 
 
 Track record in competitive programming
 
 
 Experience reviewing code in production environments
 
 
 Familiarity with multiple programming paradigms or ecosystems
 
 
 Experience explaining complex technical concepts to non-expert audiences
 
 
 
 What Success Looks Like
 
 
 
 You identify incorrect logic, inefficiencies, edge cases, or misleading explanations in model-generated code, technical concepts, and system design discussions
 
 
 Your feedback improves the correctness, robustness, and clarity of AI coding outputs
 
 
 You deliver reproducible evaluation artifacts that strengthen model performance
</div>

Frontend JavaScript Developer- Ai Training

Explore 115+ Ai computational data scientist in Houston this March. Find roles across top companies and apply now to boost your career.