Machine Learning Modeling

Machine Learning Modeling Data Jobs

6 jobs found

Today

Machine Learning Engineer, Natural Language Understanding, Proactive

Apple Santa Clara, CA

Santa Clara, CA

Today

$150k - $278k/yr Full time Ai Ml Artificial Intelligence Deep Learning

Apply Now

Job Description

Apple’s On-Device Query Understanding team is seeking a Machine Learning Engineer to research, design, implement, and evaluate machine learning models for personalized query understanding. The work supports search and assistant experiences across Apple products, with an emphasis on LLM/NLU approaches and inference optimization to achieve fast, power-efficient performance on-device.

What You’ll Do

Research, design, implement, and evaluate models that advance personalized query understanding, including user intent resolution, retrieval, and ranking.
Use natural language processing, deep learning, and large language model techniques to deliver grounded, contextually relevant responses.
Assess performance gaps in existing search and assistant systems and develop algorithms to improve model quality and key product outcomes.
Define the long-term technical vision for the team, propose roadmaps, and set measurable objectives.
Collaborate with cross-functional partners to define product requirements, establish evaluation metrics, and maximize user satisfaction.

Required Qualifications

4 or more years of experience in machine learning, natural language processing, or computer vision applied at scale.
Production software engineering experience using one or more of the following: Python, Go, C/C++, Swift, or Objective-C.
Strong communication and collaboration skills.
Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, Statistics, Physics, Mathematics, or a related field.

Preferred Qualifications

Advanced degree (Master’s or Ph.D.) in Computer Science, Statistics, or a related field, or equivalent industry experience.
Experience with Small Language Models (SLMs) and on-device LLM training, including model compression/quantization and production deployment.
Experience with large-scale query understanding, search, recommendation, or personal assistant systems.
Proficiency with machine learning frameworks such as PyTorch, JAX, TensorFlow, or XGBoost.
Background in personalization and data-driven decision making, including the ability to prototype solutions and conduct critical analysis.
Experience with Swift, Swift frameworks, or Apple platform development is a plus.
Experience with build infrastructure, release management, and CI/CD pipelines is a plus.

Key Technologies

Large Language Models (LLMs), Natural Language Understanding (NLU)
Machine learning inference optimization
PyTorch, JAX, TensorFlow, XGBoost
Swift, Objective-C
Small Language Models (SLMs), model compression/quantization
Python, Go, C/C++

Compensation & Benefits

The base pay range for this role is USD 150,400 to 277,600 per year.

Comprehensive medical and dental coverage.
Retirement benefits.
Discounted products and free services.
Reimbursement for certain educational expenses, including tuition.
Discretionary bonuses or commission payments, and relocation may be eligible.
Opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs.
Eligibility for discretionary restricted stock unit awards.
Option to purchase Apple stock at a discount by voluntarily participating in Apple’s Employee Stock Purchase Plan.

Additional information about Apple Benefits is available through Apple.

Role Details

Location: Santa Clara, CA (onsite)
Experience: 4+ years
Salary: USD 150,400 - 277,600 per yearly

View full job page →

Today

Sr Machine Learning Engineer - ML Data

Apple Cupertino, CA

Cupertino, CA

Today

$185k - $278k/yr Full time Backend Developer Ad Tech Agentic Ai

Apply Now

Job Description

Apple’s Ads Machine Learning Platform team builds secure, scalable back-end systems and ML products that help improve and scale advertising features while protecting user privacy. In this role, you’ll contribute to platform capabilities used for scalable modeling and continuous experimentation, partnering closely with ML engineers and scientists to deliver machine learning experiences that align with Apple’s privacy commitments.

Responsibilities

Design and develop secure, scalable back-end systems.
Build high-performing and elegant systems from the ground up.
Collaborate with ML engineers and scientists to create platform capabilities that enable Ads teams to improve and scale ML features, models, and applications.
Select technologies and develop solutions tailored to unique ad network challenges.
Play a meaningful role building machine learning products that support Apple’s privacy commitments and change how advertising works with data.
Contribute to reliability, simplicity, and scalability across systems and services.

Requirements

Experience writing mission-critical production code for machine learning systems.
Experience building ML infrastructure, frameworks, or services used by multiple teams.
Experience building or operating feature stores or comparable ML data infrastructure serving production models.
Experience with embedding management, including generating and versioning embeddings, refresh and retirement policy, and storing and serving for retrieval at scale.
Solid understanding of the ML lifecycle: training, evaluation, deployment, and serving/inferencing, with experience building and deploying models.
Understanding of model evaluation, train-serve skew, and data drift.
Working knowledge of deep learning architectures and training frameworks such as PyTorch or TensorFlow.
Prior experience applying ML at scale in advertising, recommender systems, information retrieval, or related domains.
Experience generating training data across multi-modal data (text, image, structured), including sampling and point-in-time correctness.
Experience building production data pipelines for ML systems where scale and performance are critical using distributed processing systems.
Experience building ML systems using batch and streaming deployments, workflow orchestration, and modern storage formats.
Strong data modeling and data architecture skills, with a high bar for system and data quality: correctness, reliability, testing, and validation.
Strong problem-solving, debugging, and performance tuning skills, with pride in automation, tooling, and CI/CD.
Results-oriented approach with effective communication in written and verbal form across technical and non-technical multi-functional teams.
Product-minded mindset with demonstrated ownership of projects.

Technologies

PyTorch, TensorFlow, LLM-based data generation or evaluation, agentic AI

Preferred Qualifications

Experience in the advertising industry.
Experience with LLM-based data generation or evaluation.
Familiarity with large-scale distributed training and its demands on data infrastructure.
Prior experience in privacy-preserving ML.
Familiarity with agentic AI.
Academic background options: PhD in Computer Science or related field with 3+ years of engineering experience and 5+ years of machine learning experience; or MS in Computer Science or related field with 6+ years of engineering experience and 5+ years of machine learning experience; or BS in Computer Science or related field with 7+ years of engineering experience and 5+ years of machine learning experience.

Pay & Benefits

Base pay range: USD 184,700 to 277,600 per year.
Participation in Apple’s discretionary employee stock programs.
Eligible for discretionary restricted stock unit awards.
Ability to purchase Apple stock at a discount if voluntarily participating in the Employee Stock Purchase Plan.
Reimbursement for certain educational expenses, including tuition.
Comprehensive medical and dental coverage.
Retirement benefits.
A range of discounted products and free services.
Discretionary bonuses or commission payments and relocation may apply.
Apple benefit, compensation, and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Location: Cupertino, CA (onsite). Minimum experience: 3 years.

View full job page →

Today

Lead Machine Learning Engineer, Human Sensing

Apple Seattle, WA

Seattle, WA

Today

$175k - $309k/yr Full time Manager Ai Ml Artificial Intelligence

Apply Now

Job Description

Apple’s Human and Object Understanding (HOUr) team is hiring a Lead Machine Learning Engineer (Technical Lead) to set technical direction for a multimodal Human Sensing team in Seattle, WA.

Partner with engineering management as the primary technical lead to define project scope, technical milestones, and roadmap execution
Set KPI targets and quality benchmarks across demographics, environmental conditions, and device use cases
Define dataset collection, annotation, and curation strategy with the Data team to reduce model blind spots
Architect and lead the team’s evaluation framework and benchmarking pipelines (custom metrics, evaluation scripts, automated tooling)
Stress-test models against production scenarios through evaluation and benchmarking automation
Lead failure mode analysis: root-cause investigation and edge-case discovery to drive model and data iterations
Coordinate day-to-day technical execution across Evaluation, Integration, and Data Operations teams
Drive model optimization in partnership with integration and other partner teams
Train, fine-tune, and run experiments with state-of-the-art vision architectures when needed for research and hypothesis validation
Maintain the team’s core codebase: author and review PRs, uphold engineering hygiene, and enable rapid iteration velocity
Communicate technical strategy, performance trade-offs, and progress to stakeholders and senior leadership
Guide and mentor junior and mid-level engineers
Stay current with machine learning trends and best practices across multimodal foundation models, computer vision, and natural language understanding

Requirements

Master’s or Ph.D. in Computer Science, Computer Engineering, or related field (or equivalent practical experience)
6+ years of industry experience in Computer Vision and Machine Learning
Proven Technical Lead or Staff-level experience driving project scoping, KPI setting, and technical initiatives across cross-functional teams
Expertise in evaluating complex ML systems, defining benchmarking methodologies, and conducting deep-dive failure analysis
Ability to coordinate engineering teams and mentor peers while partnering closely with management on roadmap execution
Strong ownership mindset, attention to detail, and agility in fast-evolving research environments
Deep proficiency in Python and PyTorch, including hands-on experience writing clean, maintainable code and managing shared repositories

Technologies

Python, PyTorch
Core ML
Quantization-aware training, knowledge distillation
Latency profiling, quantization, pruning
Multimodal foundation models, computer vision, natural language understanding
Face recognition, identity re-identification (ReID)
Foundation vision models
Large-scale Vision-Language Models (VLMs), large language models (LLMs)
Multimodal large language models (LLMs), large-scale vision-language models (VLMs)

Benefits

Comprehensive medical and dental coverage
Retirement benefits
Range of discounted products and free services
Reimbursement for certain educational expenses, including tuition
Discretionary bonuses or commission payments (may be eligible)
Relocation (may be eligible)
Opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs
Eligible for discretionary restricted stock unit awards
Can purchase Apple stock at a discount with voluntary participation in the Employee Stock Purchase Plan

Preferred Qualifications

Domain knowledge in face recognition, identity re-identification (ReID), biometrics, or visual human sensing (pose, expression, human-object interaction)
Experience collaborating with Data Collection & Annotation teams on collection protocols and active learning datasets
Experience with on-device model optimization (quantization-aware training, knowledge distillation, Core ML conversion, latency profiling)
Experience with foundation vision models or large-scale Vision-Language Models (VLMs)
Hands-on experience training and scaling multimodal LLMs or large-scale VLMs
Experience with on-device ML, model optimization (knowledge distillation, quantization, pruning), or production-grade ML pipelines
Research and innovation background shown through publications, patents, or impactful software developments

Pay & Benefits

Base pay range: $175,000 to $308,500 per year
Base pay depends on skills, qualifications, experience, and location
Apple also offers eligibility for discretionary restricted stock unit awards and an Employee Stock Purchase Plan discount (if voluntarily participating)
Note: Benefits, compensation, and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program

View full job page →

Today

Senior Machine Learning Engineer, Perception - Autonomous Driving

NVIDIA Santa Clara, CA

Santa Clara, CA

Today

$184k - $357k/yr Full time Artificial Intelligence Autonomous Driving Perception Autonomous Driving Simulation

Apply Now

Job Description

Senior Perception Engineer role focused on building and productizing autonomous driving traffic signal understanding without relying on HD maps.

Responsibilities

Design end-to-end Perception and AV stack solutions to support traffic signal detections across driving environments, from complex intersections to rural roads and highways
Conduct applied research and R&D to develop deep learning models for traffic light detection, traffic sign recognition, road marking detection, construction object detection, and text recognition for traffic signal tasks
Build generalizable approaches to support diverse ODDs and expand to new country or region requirements
Lead data-driven development by collaborating with large data collection and labeling teams to increase perception system accuracy via high-value data, including:
- Data collection prioritization and planning
- Labeling prioritization
- Labeling efficiency optimization
- Maximizing the value of collected and labeled data
Use data simulation and augmentation to address extreme scenarios
Productize perception solutions by meeting product requirements for safety, latency, and software robustness

Requirements

Minimum requirement: PhD with 4+ years, MS with 6+ years, or BS (or equivalent experience) with 8+ years in Computer Science, Computer Engineering, or a related technical field
Plus: 2+ years of technical leadership showing high technical and organizational complexity
Hands-on experience developing deep learning and algorithms for sophisticated real-world problems
Proficiency with deep learning frameworks, for example PyTorch
Experience with data-driven development and collaboration with data and ground truth teams
Strong programming skills in Python and/or C++
Outstanding communication and teamwork skills for a tightly-knit team that shares learning and expertise

Technologies

PyTorch
Python
C++
Deep learning frameworks
Transformers
BEV architectures
Visual Language Models

Benefits

Equity and benefits eligibility

Ways to Stand Out

Proven expertise developing generalizable perception solutions for autonomous driving or robotics using deep learning with cameras
Hands-on experience developing and deploying DNN-based solutions to embedded platforms for real-time applications
Proven deep learning expertise supported by technical publications in leading conferences and journals
Expertise with Visual Language Models, Transformers, BEV architectures, and modern traffic signal perception techniques, including experience with complex object detection and recognition (a plus)

Location: Santa Clara, CA (onsite)

Salary: USD 184,000 - 356,500 per year

View full job page →

Today

Sr. Machine Learning Engineer - Answers, Knowledge & Information (AKI)

Apple Santa Clara, CA

Santa Clara, CA

Today

$175k - $309k/yr Full time Ai Engineer Ai Ml Artificial Intelligence

Apply Now

Job Description

Apple’s Geo domain team is seeking a Senior Machine Learning Engineer to build machine learning and LLM-based systems that interpret user queries, rank documents, and surface useful local answers through Siri and Spotlight. The role focuses on improving search quality across the full pipeline, from query understanding to retrieval and ranking.

Role Overview

As a senior member of the AKI (Answers, Knowledge & Information) team, you will own end-to-end machine learning development to enhance how local information is understood and delivered. You will work on models and systems that support query understanding, document ranking, and overall search relevance.

Key Responsibilities

Own the entire ML development cycle, from opportunity analysis, exploration, and prototyping through data collection, feature engineering, training, evaluation, and production deployment.
Lead development of machine learning models to improve search quality across retrieval, ranking, reranking, and query understanding.
Enhance search quality and user experience by applying techniques such as learning-to-rank, embedding models, contrastive learning, multi-task learning, and reinforcement learning where appropriate.
Provide technical leadership by mentoring junior engineers and contributing to the architecture of ML systems and model design.
Translate product requirements into modeling tasks and engineering tasks.

Required Qualifications

8+ years of experience in information retrieval, natural language processing, machine learning, or deep learning.
Deep understanding of machine learning theory, including supervised learning, ranking models, embeddings, representation learning, and evaluation metrics.
Proven ability to apply advanced ML techniques to improve search relevance and retrieval quality at scale.
Comfort leading experimentation, offline evaluation, and online A/B testing to support iterative improvements in search quality.
Excellent interpersonal skills, with the ability to work independently and collaboratively.
Master’s Degree in Computer Science or equivalent experience in machine learning or a related field.

Preferred Qualifications

Advanced diploma in AI, Machine Learning, Computer Science, or Mathematics.

Technology Focus

LLMs

Location

Santa Clara, CA (onsite)

Compensation

Base pay range: USD 175,000 - 308,500 per year.

Benefits

Comprehensive medical and dental coverage
Retirement benefits
Discounted products and free services
Reimbursement for certain educational expenses, including tuition
Participation in Apple’s discretionary employee stock programs (eligible for discretionary restricted stock unit awards)
Ability to purchase Apple stock at a discount if voluntarily participating in the Employee Stock Purchase Plan
Discretionary bonuses or commission payments as well as relocation (might be eligible)

Education

Master’s Degree in Computer Science.

View full job page →

Today

Data Scientist ll - RiskOS

Socure Seattle, WA

Seattle, WA

Today

$140k - $170k/yr Full time Artificial Intelligence Big Data Data Pipeline

Apply Now

Job Description

Socure’s RiskOS team is building practical protections for workforce identity and hiring fraud, with a focus on Workforce Verification. In this role, you’ll own the end-to-end data science lifecycle for workforce risk use cases, combining fraud analytics with NLP and Generative AI to deliver models, rules, and GenAI components that work inside RiskOS workflows.

Based in Seattle, WA (onsite), you will partner across RiskOS and Workforce product teams, engineering, and go-to-market stakeholders to turn model and rule performance into measurable outcomes for customers.

What you’ll do

Own the full data science lifecycle for Workforce Verification use cases on RiskOS, from data exploration and hypothesis generation through development, evaluation, deployment, and ongoing monitoring.
Explore workforce-related data sources including applications, resumes, device and behavioral telemetry, background checks, and ATS/HRIS integrations to identify fraud patterns such as fake resumes, identity rental, deepfake interviews, and injection attacks.
Design, implement, and iterate on rules, conditions, and heuristic logic in RiskOS workflows to detect high-risk workforce events (for example repeated identities across multiple resumes, suspicious device patterns, and anomalous hiring flows).
Develop and evaluate machine learning models for workforce risk and identity assessment, including scoring applicants for fraud risk, clustering related identities, and anomaly detection over hiring funnels. Apply Socure identity and device signals where appropriate.
Collaborate with RiskOS and Workforce teams on GenAI-powered features such as the Resume Verification Agent and explanation agents, including defining inputs and outputs, building evaluation datasets, and setting quantitative and qualitative evaluation frameworks for LLM components.
Work closely with engineering to productionize models, rulesets, and GenAI components in RiskOS by defining interfaces, supporting integration and testing, and contributing to monitoring, alerting, and feedback loops.
Translate model and rule performance into customer-facing narratives with Product, Workforce GTM, and solution consulting, including examples like blocking fake applicants, reducing deepfake interviews, or preventing identity rental in hiring.
Incorporate customer feedback and outcome data to improve Workforce Verification logic and models, including supporting experimentation and offline “test harness” design to evaluate new workflows and templates safely.
Operate with a product mindset and strong ownership by documenting assumptions, decisions, and evaluation results, communicating trade-offs clearly, and surfacing risks, limitations, and opportunities.

What you bring

Bachelor’s or Master’s degree in a quantitative field (Computer Science, Statistics, Mathematics, Engineering, or related) or equivalent practical experience.
3–6 years of hands-on experience in data science, machine learning, or applied analytics, with meaningful work in fraud, risk, trust & safety, or workforce/hiring analytics preferred.
Experience owning end-to-end analytics and/or model development projects, including problem framing, data wrangling, feature engineering, model training, and evaluation and deployment support.
Strong proficiency in Python and SQL, with experience using common ML and data science libraries such as pandas, scikit-learn, XGBoost, PySpark, or similar tools.
Comfort working with large, messy, heterogeneous datasets (including JSON workflows, logs, event streams, and third-party enrichments) and building reusable abstractions or utilities.
Exposure to Natural Language Processing and/or unstructured text analytics such as resume or document parsing, entity extraction, similarity search, or basic embedding-based methods in real-world products.
Some hands-on experience with Generative AI or LLM-based products, such as commercial LLM APIs, prompt design, RAG-style retrieval, or evaluation of LLM outputs, with interest in deepening this skill set.
Strong analytical and problem-solving skills, including reasoning about ambiguous signals and adversarial behavior in fraud or workforce contexts.
Ability and willingness to take on light data engineering and production-oriented tasks when needed (for example ETL transforms, contributing to Airflow/Spark jobs, or instrumenting basic monitoring) in partnership with engineering.
Clear, concise communication skills for explaining complex analyses, models, and GenAI behavior to non-technical stakeholders.
A bias toward ownership, learning, and collaboration, comfortable working in a fast-paced environment with guidance from senior data scientists while expanding autonomy.

Technologies you’ll use

Python, SQL, pandas, scikit-learn, XGBoost, PySpark
Natural Language Processing, Generative AI, LLM-based products
Commercial LLM APIs, RAG-style retrieval
Airflow, Spark, ETL, JSON

Compensation

USD 140,000 - 170,000 per year

View full job page →

Machine Learning Modeling Data Jobs

Machine Learning Engineer, Natural Language Understanding, Proactive

Sr Machine Learning Engineer - ML Data

Lead Machine Learning Engineer, Human Sensing

Senior Machine Learning Engineer, Perception - Autonomous Driving

Sr. Machine Learning Engineer - Answers, Knowledge & Information (AKI)

Data Scientist ll - RiskOS

Get Machine Learning Modeling Data Jobs alerts