Predictive Modeling

Predictive Modeling Developer Jobs

11 jobs found

6d ago

Machine Learning Engineer - AI Trainer

DataAnnotation Massachusetts 🇺🇸 Remote

Massachusetts

6d 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 help evaluate and train AI systems focused on quantitative reasoning. This is a remote, contract role with flexible project selection after completing a short assessment.

Role Overview

You will review AI-generated quantitative outputs and contribute to the creation and improvement of training and benchmark tasks. Work is completed remotely using projects provided through the platform after you pass the initial assessment.

Key Responsibilities

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

Requirements

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 related field.
Some coding experience is required, with comfort writing and reviewing analytical code end-to-end.
Practical experience applying statistical methods, predictive modeling, and experiment design, including examples such as A/B testing, hypothesis testing, regression, classification, and time-series forecasting.
English fluency at 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

Kaggle
AWS
GCP

Compensation and Job Details

Job type: contract
Location: Massachusetts (remote)
Rate: USD 50 - 100 per hourly

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: projects are paid hourly, up to $60 USD per hour, with opportunities for higher-paying projects based on strong performance.
Impact: contribute to AI systems designed to reason about data and analytics.

Payment and Eligibility Notes

Payment is made via PayPal.
They will never ask you for money.
The role is available only to candidates in the US, Canada, UK, Ireland, Australia, and New Zealand.

How to Apply

After signing up for an account, you will complete a short assessment (serving as the company’s version of an interview). If you pass, you will receive an email confirmation, and paid work will become available on the platform.

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15d ago

Machine Learning Engineer, Growth

Whatnot Seattle, WA 🇺🇸 Remote

Seattle, WA

15d ago

$190k - $280k/yr Full time Artificial Intelligence Data Engineer Data Pipeline

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Job Description

Whatnot is seeking a Machine Learning Engineer, Growth to join the Buyer Growth team in Seattle, WA (remote). In this role, you will build and own machine learning models that improve onboarding personalization and user targeting across acquisition and engagement channels, supporting measurable buyer growth and first-time conversion.

What you’ll work on

Design, develop, and productionize ML models for acquisition, activation, and retention, including ranking models, targeting systems, and uplift modeling.
Own the full machine learning lifecycle: data pipelines, feature engineering, model training, deployment, and online experimentation.
Build feedback loops from postbacks, conversions, and downstream revenue signals to improve model performance over time.
Identify and prioritize high-impact growth opportunities for machine learning, partnering with product, engineering, data, and marketing stakeholders.
Drive technical excellence by establishing ML best practices across the Buyer Growth team.

What you bring

5+ years of industry experience building and deploying ML systems at scale.
Proven experience leading end-to-end ML projects with measurable business outcomes.
Strong expertise in personalization, ranking, or user modeling, along with strong intuition for user behavior in consumer products.
Advanced proficiency in Python and SQL, plus common ML frameworks such as PyTorch, TensorFlow, and XGBoost.
Strong communication and leadership skills, with the ability to influence roadmap decisions and align cross-functional teams.
Preferred: Experience building ML applications in e-commerce or social products.
Preferred: Growth-domain experience such as user segmentation, retention modeling, large-scale recommendation systems, notification ranking, and related areas.

Tools you’ll use

Python, SQL, PyTorch, TensorFlow, XGBoost

Benefits that support your life outside work

Flexible Time Off Policy and company-wide holidays, including a spring and winter break
Health Insurance options: Medical, Dental, Vision
Work From Home Support
Home office setup allowance
Monthly allowances: cell phone and internet, and a wellness allowance
Care benefits
Annual allowance towards childcare
Lifetime benefit for family planning, such as adoption or fertility expenses
Retirement: 401k offering for Traditional and Roth accounts in the US (employer match up to 4% of base salary) and Pension plans internationally
Monthly allowance to dogfood the app
Parental Leave: 16 weeks of paid parental leave plus one month of gradual return to work

Compensation Range: $190K - $280K. EOE.

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15d ago

Lead Machine Learning Engineer

Disney Entertainment and ESPN Product & Technology San Francisco, CA

San Francisco, CA

15d ago

$188k - $252k/yr Full time Manager Ai Ml Artificial Intelligence

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Job Description

The Lead Machine Learning Engineer will help shape and operationalize personalization technology for Disney+ and Hulu. This role focuses on ideation through productionization of recommendation algorithms across the full recommendation stack, using modern AI and LLM techniques alongside rigorous offline and online evaluation.

Responsibilities

Ideate, develop, iterate, and productionize personalization algorithms, including core ranking, content and user understanding models and graphs, candidate retrieval, and post-ranking systems.
Apply modern AI and LLM techniques to recommendation systems, including generating and improving recommendations, strengthening system evaluation, and accelerating model development and improvement.
Provide technical insight on recommendation approaches, evaluation methodology, and defining data, features, and objectives for models, while supporting other scientists in shaping and productionizing their ideas.
Drive the technical vision and innovation agenda for personalization by identifying high-impact opportunities and influencing how the team executes.
Design and run rigorous offline and online experiments, and contribute to improving evaluation systems and evaluation methodology.
Collaborate within the team and across Engineering, Product, and Data partners by communicating methodologies clearly to technical and non-technical audiences and managing stakeholder expectations.
Build production-worthy, maintainable systems that are easy to iterate on, and uphold strong standards for development, testing, and deployment, with readiness to support production issues when needed.

Requirements

7+ years of experience developing machine learning models and deploying them to production systems.
Strong background in applied ML science, end-to-end ML engineering, or a blend of both, with experience in recommendation systems modeling.
Hands-on experience with AI and LLM techniques and a solid understanding of the modern AI landscape.
Proficiency with tools and frameworks such as PyTorch, TensorFlow, Databricks, Spark, and SQL.
In-depth understanding of modern machine learning methods, models, and their mathematical foundations.
Strong written and verbal communication skills.
A collaborative, personable working style that supports teamwork across organizations rather than working in isolation.

Preferred Qualifications

PhD in computer science, statistics, math, or a related quantitative field.
Publications or papers in machine learning or AI, particularly in recommender systems.
Production experience developing content recommendation algorithms at scale.
Experience with reinforcement learning or related sequential decision-making approaches.
Experience with recommendation system evaluation methodology, including offline evaluation and A/B experimentation.

Technologies

PyTorch
TensorFlow
Databricks
Spark
SQL
AI
LLM

Compensation and Benefits

Salary: USD 187,900 - 252,000 per yearly.

A bonus and/or long-term incentive units may be provided as part of the compensation package.
The full range of medical, financial, and/or other benefits (dependent on the level and position offered).

Location

San Francisco, CA (onsite).

Education

BS or MS in Computer Science, Engineering, or a related field.

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17d ago

Machine Learning Engineer Graduate (Commerce Ads) - 2027 Start

TikTok San Jose, CA

San Jose, CA

17d ago

$128k - $256k/yr Full time Ad Ranking Ai Ml Artificial Intelligence

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Job Description

Join TikTok as a Graduate Machine Learning Engineer supporting Commerce Ads, starting in 2027 at the San Jose office on an onsite basis. In this role, you will help build scalable machine learning systems and models that strengthen ads ranking quality while optimizing how advertisers’ marketing strategies perform.

The work blends strong software fundamentals with applied machine learning, including experimentation to improve model accuracy and collaboration across product and design teams to shape next-generation shopping experiences on TikTok.

What you’ll do

Develop highly scalable machine learning systems and state-of-the-art models to improve ads ranking quality and optimize advertisers’ marketing strategies, including applications such as click-through rate prediction, conversion rate prediction, intelligent format selection, and user journey optimization.
Explore, develop, and run experiments on new features aimed at improving model accuracy.
Work with ads platform objectives and use modern machine learning to enhance ads relevance, quality, and the quantity delivered to end users.
Collaborate with Product Managers, Designers, and other teams to help define and build next-generation shopping experiences on TikTok.

Qualifications

Completing or recently completed a Bachelor’s degree or above in Computer Science, Computer Engineering, or a related technical discipline.
Strong programming ability, including Go, C/C++, and Python; familiarity with data structures and algorithms; and comfort working in a Linux development environment.
Analytical problem-solving skills, with essential knowledge and skills in statistics.
Solid theoretical grounding in machine learning and deep learning concepts, including architectures such as CNN, RNN, and LSTM.
Familiarity with the architecture and implementation of at least one mainstream ML framework, including TensorFlow, PyTorch, or MXNet.

Technology focus

Go, C/C++, Python, Linux
CNN, RNN, LSTM
TensorFlow, PyTorch, MXNet
Spark

Compensation & benefits

Base salary range: USD 128,000 - 256,000 per year
Day one access to medical, dental, and vision insurance
401(k) savings plan with company match
Paid parental leave
Short-term and long-term disability coverage
Life insurance
Wellbeing benefits
10 paid holidays per year
10 paid sick days per year
17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure)

Preferred qualifications

Knowledge in at least one of: ads bidding & auction, ads quality control, or online advertising systems, including familiarity with terms such as CPC/CPM, CTR/CVR, Ranking/Targeting, Conversion/Budget, Campaign/Creative, and Demand/Inventory, as well as DSP/RTB.
Experience with resource management and task scheduling for large-scale distributed software, such as Spark and TensorFlow.
Relevant work or research experience in search and recommendation.

Additional application details

Job code: A39632
Location: San Jose
Employment type: Regular
Successful candidates must be able to commit to an onboarding date by the end of the year. Please state availability and graduation date clearly in your resume.
Candidates can apply to a maximum of two positions and will be considered in the order you apply.
Applications will be reviewed on a rolling basis, and candidates are encouraged to apply early.
For Los Angeles County (Unincorporated) candidates: qualified applicants with arrest or conviction records will be considered in accordance with applicable laws, including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. The role may involve interacting with clients/colleagues (including occasional unsupervised contact), handling confidential information, and managing access to IT systems, which may relate to conditional employment decisions.
TikTok accommodations: TikTok provides reasonable accommodations in recruitment processes for candidates with disabilities, pregnancy, sincerely held religious beliefs, or other reasons protected by applicable laws. Requests can be made at https://tinyurl.com/RA-request.

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17d ago

Machine Learning Engineer

Harvard University Boston, MA

Boston, MA

17d ago

Full time Ai Ml Artificial Intelligence Data Pipeline

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Job Description

Harvard Medical School’s Core for Computational Biomedicine (CCB) is seeking a Machine Learning Engineer to lead the development and deployment of medical large language models.

Responsibilities

Develop, implement, and optimize medical large language models for medical education and clinical decision support
Collaborate with interdisciplinary teams including biologists, clinicians, and data scientists to translate domain requirements into computational solutions
Monitor and apply advances in deep learning and machine learning to keep models state-of-the-art
Build infrastructures for data transformation and data ingestion
Create AI models that generate predictions from large-scale data
Communicate the usefulness of AI models to non-technical stakeholders
Transform machine learning models into APIs so other applications can interact with them
Use expert knowledge to lead research AI and data science projects

Requirements

Minimum of seven years post-secondary education or relevant work experience
Master’s or PhD in Computer Science, Computational Biology, or a related field strongly preferred
Minimum of 3 years hands-on experience developing complex deep learning solutions for scientific challenges
Proficiency in the Python deep learning stack, including expertise with PyTorch, Numpy, and related packages
Experience working with and processing large and diverse datasets, especially medical texts, journals, or electronic health records
Ability to collaborate with non-technical stakeholders such as doctors and medical researchers
Experience using experiment tracking and project management tools, including Weights & Biases
Prior experience in fine-tuning large language models for specific tasks
Demonstrated ability to optimize deep learning models for improved performance and efficiency
Understanding of biology and/or medicine to connect machine learning to medical applications
Track record of publications in technical conferences or journals

Technologies

Python
PyTorch
Numpy
Weights & Biases

Location & Work Format

Boston, MA (hybrid)
Standard schedule: 35 hours per week
Some duties may be performed at a non-Harvard location as determined by unit leadership
For hybrid employees not working at a Harvard location, work must be performed in a Harvard registered state in compliance with the University’s Policy on Employment Outside of Massachusetts
When not working at a Harvard/Harvard-designated location, additional requirements may apply based on interview details
Some visa types and funding sources may limit work location
Individuals must meet work location sponsorship requirements prior to employment
Interviews and onboarding are currently being conducted remotely and virtually

Additional Information

Visa sponsorship: Harvard University is unable to provide visa sponsorship for this position
Pre-employment screening: Identity, Education, Criminal
Application status: Careers@Harvard portal
Salary grade level: 060

Benefits

Generous paid time off including parental leave
Medical, dental, and vision coverage starting on day one
Retirement plans with university contributions
Wellbeing and mental health resources
Support for families and caregivers
Professional development opportunities including tuition assistance and reimbursement
Commuter benefits, discounts, and campus perks

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22d ago

Machine Learning Engineer

Photon New Jersey

New Jersey

22d ago

Full time Python Advanced Analytics Ai Ml

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Job Description

Photon seeks a skilled Machine Learning Engineer for an onsite role in New Jersey. The position focuses on designing and deploying analytics models through statistical and machine learning approaches, collaborating with product and engineering teams to solve complex business problems, and delivering end-to-end ML solutions in production using Python, Spark, and Databricks.

Responsibilities

Assess business use cases and design analytics models using statistical and machine learning methods tailored to specific requirements.
Develop machine learning algorithms to personalize customer experiences and generate actionable business insights.
Apply data mining and ML techniques, including forecasting, prediction, segmentation, recommendation, and fraud detection.
Augment company data with third-party sources to broaden analytics capabilities.
Improve data collection processes to capture information essential for analytics systems.
Prepare raw data for analysis, including cleaning, imputing missing values, and standardizing formats using Python data frameworks (Pandas, NumPy).
Implement ML models with attention to performance and scalability using PySpark in Databricks.
Design and build infrastructure to support large-scale data analytics and experimentation.
Utilize tools such as Jupyter Notebooks for data exploration and model development.

Requirements

Bachelor's or graduate degree in Computer Science, Mathematics, Physics, or related fields; PhD preferred but not required.
Minimum five years of experience in data analytics with a strong understanding of core statistical algorithms, including classification and regression.
Strong experience with Python-based machine learning libraries such as scikit-learn, TensorFlow, and PyTorch.
Proficiency with analytics platforms like Databricks for large-scale data processing.
At least four years of continuous experience with Spark, particularly PySpark.
Hands-on experience with data processing and analysis tools including Pandas, NumPy, and Jupyter Notebooks.

Technologies

Python
Spark
Databricks
Pandas
NumPy
Jupyter Notebooks
PySpark
scikit-learn
TensorFlow
PyTorch

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1mo ago

Senior Machine Learning Engineer

Disney Entertainment and ESPN Product & Technology New York, NY

New York, NY

1mo ago Closed

$149k - $199k/yr Full time Ai Ml Analytics Apache Airflow

This position is no longer accepting applications (closed Aug 21, 2026).

Job Description

Senior Machine Learning Engineer (Individual Contributor) on-site in New York, NY for Disney Entertainment and ESPN Product & Technology, focused on personalization and recommendation algorithms for Disney+ and Hulu.

Responsibilities

Develop and maintain state-of-the-art personalization and recommendation models, serving production systems and explaining methodologies to both technical and non-technical stakeholders.
Design and sustain ETL pipelines and data workflows with Airflow and Jenkins; deploy scalable streaming and batch data pipelines to support petabyte-scale datasets.
Establish and enforce best practices for algorithm development, testing, and deployment, while evolving standards over time.
Collaborate with product and business stakeholders to uncover new personalization opportunities and coordinate with data teams to improve data collection, experimentation, and analysis.

Requirements

5+ years of experience developing machine learning models, performing large-scale data analysis, and/or data engineering.
5+ years writing production-grade, scalable code in Python and SQL.
3+ years developing algorithms for deployment to production systems.
Strong understanding of modern machine learning concepts, models, and their mathematical underpinnings.
Experience deploying and maintaining pipelines and building big-data solutions with Databricks, S3, and Spark.
Ability to gauge the complexity of ML problems and apply simple, effective approaches when appropriate.
Excellent written and verbal communication skills.
MS or PhD in statistics, mathematics, computer science, or related quantitative field.
Production experience developing content recommendation algorithms at scale.
Experience delivering end-to-end ML pipelines: data extraction, data mining, model training, feature development, testing, and deployment.
Familiarity with metadata management, data lineage, and data governance principles.
Experience loading and querying cloud-hosted databases.