Machine Learning & Ai

Machine Learning & Ai Engineer Jobs

26 jobs found

Today

Machine Learning Engineer, Data Curation - Autonomous Vehicles

NVIDIA Santa Clara, CA

Santa Clara, CA

Today

$152k - $288k/yr Full time Artificial Intelligence Autonomous Driving Perception Data Curation

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Job Description

Join NVIDIA’s Autonomous Vehicles Data Curation team to apply deep learning to search, curate, and evaluate datasets and ground truth that support self-driving car capabilities.

Responsibilities

Keep current with deep learning research and innovations; implement and experiment with new ideas
Work with researchers and engineers to convert research into reliable, industrial-strength machine learning models
Take machine learning work from initial evaluation and experimentation through to shipping
Define, collect, and curate training and evaluation datasets, emphasizing scenario coverage and label quality
Develop vision-language models and embeddings to enable scenario search, classification, and automated data curation
Build training pipelines and scalable inference systems using PyTorch, TensorFlow, TensorRT, Python, and C++

Requirements

PhD with 1+ year of relevant experience, or MS (or equivalent experience) with 5+ years in a related technical field
Relevant fields: Computer Science, Computer Engineering, or closely related technical discipline
Proven experience building robust software
Interest in Artificial Intelligence for robotics and autonomous navigation
Motivation to learn new topics and solve hard problems
Knowledge of mathematics
Experience in Deep Learning / Machine Learning, including background in Computer Vision and/or multimodal learning
Programming and debugging skills in C++ and/or Python
Strong communication and analytical skills; ability to collaborate with multiple teams in a dynamic environment

Technologies

PyTorch
TensorFlow
TensorRT
Python
C++

Benefits

Equity and benefits
Comprehensive benefits package

Ways to Stand Out

Experience applying state-of-the-art AI methods to Computer Vision and Autonomous Vehicles problems
Experience with Unsupervised or Self-supervised Learning and contrastive representation learning
Experience with vision-language models, agentic search, or automated dataset quality evaluation

Location: Santa Clara, CA (onsite)

Salary: USD 152,000 - 287,500 per year

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3d ago

Senior Staff Audio Machine Learning Engineer

Boston Dynamics Waltham, MA

Waltham, MA

3d ago

$180k - $220k/yr Full time Acoustic Change Detection Ai Engineer Artificial Intelligence

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Job Description

Boston Dynamics is seeking a Senior Staff Audio Machine Learning Engineer to support the Spot Sensing team in building the next generation of acoustic intelligence for industrial machinery. In this onsite role in Waltham, MA, you will help evolve Acoustic Change Detection (ACD) by transforming both beamformed and raw audio into signals that support machinery prognostics, and by unifying acoustic features with other modalities for prescriptive maintenance outcomes.

You will work across the full pipeline, from signal processing and model architecture through deployment practices for industrial customers, partnering with the broader Spot Apps organization to translate audio insights into machine health indicators and operator-ready recommendations.

Responsibilities

Design, refine, and scale digital signal processing and machine learning pipelines for the Acoustic Change Detection (ACD) system.
Lead improvement and modernization of the acoustic detection stack, including transitioning from unsupervised models (for example, BGMM) to state-of-the-art anomaly architectures and architecting end-to-end supervised multimodal pipelines for automated fault diagnosis.
Partner with the broader Spot Apps organization to integrate acoustic insights with visual, thermal, and VLM/LLM data streams into unified machine health indicators, supporting both mechanical diagnoses and recommended corrective actions for plant operators.
Benchmark, optimize, ship, monitor, and continuously improve the solution for industrial customers.

Requirements

7+ years of deep practical expertise in audio feature extraction, audio fingerprinting (e.g., Shazam, DMCA enforcement), and segmentation (e.g., DCASE), applying machine learning to audio data (beamformed and raw) for anomaly detection, preferably in industrial environments or similar problem domains.
Advanced proficiency in Python and C++, with strong numerical and scientific stacks such as NumPy, SciPy, scikit-learn, and PyTorch.
Expertise in both time domain and frequency domain data analysis.
Expertise in multi-channel array processing, including beamforming (Delay-and-Sum, MVDR, null-steering), Direction of Arrival (DoA) estimation, and synthetic aperture techniques.
Expertise in unsupervised and supervised classification architectures for anomaly detection under real-world conditions.

Technologies

Python, C++, NumPy, SciPy, scikit-learn, PyTorch
Shazam, DCASE, BGMM
Delay-and-Sum, MVDR, null-steering, Direction of Arrival (DoA), synthetic aperture
VLM, LLM, TypeScript

Benefits

Medical
Dental
Vision
401(k)
Paid time off
Annual bonus structure

Bonus Points

Hands-on experience in cross-modal fusion combining audio representations with computer vision, thermal imaging, or multimodal foundation models/VLMs.
Background in rotating machinery health monitoring (bearings, gearboxes, pumps) and familiarity with mechanical vibration/acoustic failure standards.
Familiarity with TypeScript and modern web services for integrating work into Orbit, the fleet management software.

Location: Waltham, MA (onsite)
Compensation: USD 180,000 - 220,000 per year
Minimum experience: 7 years

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12d ago

Staff Machine Learning Engineer

BD Laguna Hills, CA

Laguna Hills, CA

12d ago

$130k - $207k/yr Full time Ai Foundation Models Ai Ml Artificial Intelligence

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Job Description

BD is building clinically meaningful AI and machine learning that supports continuous physiological monitoring, disease detection, and predictive clinical decision support. This Staff Machine Learning Engineer role (onsite) focuses on end-to-end algorithm development and deployment across cloud systems and edge medical devices, using multi-modal healthcare data.

What you’ll do

Lead the design, development, validation, and deployment of AI/ML algorithms for continuous physiological monitoring, novel vital sign and physiological parameter development, disease detection and risk stratification, and early warning systems.
Develop models using multi-modal data sources including physiological waveforms and time-series signals such as PPG, blood pressure, and capnography, along with bedside and wearable sensor data, electronic health records, structured clinical data, and related monitoring inputs.
Translate clinical and physiological understanding into robust algorithm design, including feature selection, model architecture, performance targets, and clinically interpretable outputs.
Build end-to-end algorithm pipelines covering data ingestion, signal quality assessment, annotation, feature extraction, model training, validation, robustness testing, and post-market performance monitoring where applicable.
Partner with clinical, medical affairs, regulatory, quality, and product teams to align algorithm development with clinical context, usability, safety, and regulatory expectations.
Optimize and implement algorithms for both cloud environments and edge or embedded medical devices, addressing latency, memory, compute, power, cybersecurity, and reliability constraints.
Support verification, validation, documentation, risk analysis, and design controls for regulated medical technology products.
Contribute to intellectual property generation, technical strategy, research roadmaps, and external scientific engagement.

What you bring

7+ years of industry experience in AI/ML, algorithm development, biomedical signal processing, healthcare analytics, medical devices, or related technical areas.
Master’s or PhD degree preferred in Electrical Engineering, Biomedical Engineering, Computer Science, Data Science, Applied Mathematics, Statistics, Computational Biology, or a related engineering or quantitative field.
Deep expertise in machine learning and AI model development, including classical and modern approaches.
Hands-on experience with physiological time-series data, biomedical signals, medical device data, or clinical datasets.
Strong understanding of human physiology as it relates to patient monitoring.
Demonstrated experience taking algorithms from early feasibility through productization or deployment.
Experience working with multi-modal healthcare data such as sensor signals, EHR data, imaging data, lab data, and clinical outcomes.
Strong programming skills in Python and experience with ML/AI frameworks such as PyTorch, TensorFlow, and scikit-learn (or equivalent tools).
Experience with cloud-based algorithm development and deployment using Azure, AWS, or GCP.
Experience optimizing models for deployment in constrained environments including embedded systems, edge devices, or near-real-time medical technology platforms.
Strong model evaluation skills including sensitivity, specificity, AUROC, calibration, false alarm burden, clinical utility, robustness, and generalizability.
Excellent communication skills across engineering, clinical, regulatory, and business stakeholders.

Tools you may use

Python, PyTorch, TensorFlow, scikit-learn
Azure, AWS, GCP
Transformer-based models and foundation-model approaches where appropriate

Benefits

Medical, dental, vision, health savings and flexible spending accounts
Life and disability insurance
Wellness resources and mental health support
Disease management programs
401(k) and deferred compensation programs
Financial counseling, DailyPay
Educational savings resources and educational assistance
Paid time off, company holidays
Parental leave, adoption assistance
Backup care, caregiving support, employee assistance programs
Commuter benefits
Pet insurance, legal services
Associate discount programs
Bereavement leave, military leave, personal leave, family and medical leave, jury duty leave

Location: Laguna Canyon, CA (onsite), USA (primary work location: CA - Irvine Laguna Canyon).
Salary range: USD 129,600 to 207,400 per year.

Preferred qualifications

Experience developing AI/ML algorithms for regulated medical devices, digital health products, clinical decision support tools, or Software as a Medical Device (SaMD).
Familiarity with medical device development practices including design controls, risk management, verification and validation, human factors, clinical performance evaluation, and regulatory documentation.
Experience with signal quality assessment, artifact detection, missing-data handling, sensor fusion, uncertainty quantification, and explainable AI.
Familiarity with MLOps and model lifecycle management including version control, data governance, automated testing, and post-deployment monitoring.

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14d ago

Senior Software Engineer- Machine Learning

Anduril Industries Waltham, MA

Waltham, MA

14d ago

$190k - $252k/yr Full time Anomaly Detection API APIs

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Job Description

Join Anduril Industries’ Battlespace Awareness Command and Control Software team in Waltham, MA onsite and help build the infrastructure that powers core tools and practical ML workflows. This role blends software engineering support with ML infrastructure development, focused on system parameter optimization and performance regression detection in CI.

Anduril offers a comprehensive, competitive benefits package available at little to no cost to employees, designed to support you across health, recovery, and what comes next.

Responsibilities

Provide software engineering and development support for multiple core tools used by the team
For candidates with an ML background, help stand up new ML infrastructure that improves how the team optimizes system parameters and detects performance regressions in CI

Requirements

Professional experience in one or more of Python, Rust, C++, or C, with a clear track record using these languages professionally
Solid software engineering fundamentals, including object-oriented programming, functional programming, and REST API design
Experience building low-latency or real-time software
Experience with software testing, including Robot Framework testing and integration test development
Comfort using AI coding assistants (Claude or Codex) as part of day-to-day workflow
Experience with GitHub and CI/CD pipelines
Machine learning background in:
- Hyperparameter optimization
- Anomaly detection
- Explainable ML (e.g., Bayesian ML)
Must be authorized to work in the United States
Eligible to obtain and maintain an active U.S. Secret security clearance

Technologies

Python, Rust, C++, C
REST API
Robot Framework
GitHub, CI/CD pipelines
Claude, Codex
Hyperparameter optimization, Anomaly detection, Explainable ML, Bayesian ML
PyTorch, FastAPI
TypeScript, JavaScript, React, NodeJS
CesiumJS

Preferred Qualifications

TypeScript or JavaScript, React, and/or NodeJS
PyTorch
Python FastAPI
CesiumJS
Experience with faster-than-real-time (FTRT) simulation
Experience building Slackbot integrations
Master’s, PhD, or 2–3+ years of professional experience in machine learning, especially model deployment

Salary: USD 190,000 - 252,000 per year.

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15d ago

Sr Machine Learning Engineer

PayPal San Jose, CA

San Jose, CA

15d ago

$160k - $237k/yr Full time Cloud Ml Data Analysis Data Pipeline

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Job Description

Build and ship machine learning solutions that improve products and customer experiences in a hybrid role based in San Jose.

Responsibilities

Design, develop, and optimize machine learning models for multiple use cases
Preprocess and analyze large datasets to extract actionable insights
Deploy machine learning solutions into production using appropriate tools and frameworks
Partner with cross-functional teams to integrate ML models into products and services
Monitor and evaluate deployed model performance

Requirements

3+ years relevant experience and a Bachelor’s degree, or an equivalent combination of education and experience
Experience working with machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn
Familiarity with cloud platforms including AWS, Azure, and GCP, plus tools for data processing and model deployment
Several years of experience designing, implementing, and deploying machine learning models

Technology

TensorFlow
PyTorch
scikit-learn
AWS
Azure
GCP

Location and Work Model

San Jose, CA (Hybrid)
For the majority of employees, balanced hybrid model includes:
- 3 days in the office for in-person collaboration
- 2 days at your choice of either the PayPal office or your home workspace
Travel: 0
Primary location pay range: $159,500.00 - $236,500.00 annually
Additional locations: None currently assigned

Compensation

Annual salary range: USD 159,500 - 236,500
Additional compensation may include: annual performance bonus, equity, or other incentive compensation as applicable

Benefits

Generous paid time off
Healthcare coverage for you and your family
Resources to create financial security and support mental health
Comprehensive, choice-based programs to support personal wellbeing (physical, emotional, and financial)

Subsidiary: PayPal

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15d ago

Senior Machine Learning Engineer – End-to-End Autonomous Driving

Qualcomm Technologies, Inc. San Diego, CA

San Diego, CA

15d ago

$141k - $211k/yr Full time Senior Artificial Intelligence Autonomous Driving

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Job Description

Build next-generation end-to-end driving intelligence with Qualcomm’s Autonomous Driving AI team. This onsite role in San Diego, CA focuses on developing deep learning systems that translate multimodal sensor inputs into safe, reliable driving behavior, supported by training infrastructure, simulation, and safety-critical evaluation.

Qualcomm offers a competitive annual discretionary bonus program, an opportunity for annual RSU grants, and a highly competitive benefits package. The annual pay range is USD 140,800 - 211,200.

What You’ll Do

Design, develop, and optimize state-of-the-art end-to-end autonomous driving models.
Build scalable machine learning pipelines for data processing, training, validation, and deployment.
Develop multimodal deep learning architectures that incorporate vision, map, route, and vehicle context.
Create behavioral planning and trajectory generation models.
Work on goal-conditioned driving systems and controllable AI planning frameworks.
Develop evaluation methodologies and metrics to measure model quality, safety, and driving performance.
Implement simulation-based validation and closed-loop evaluation frameworks.
Investigate failure cases and long-tail scenarios to improve robustness and generalization.
Apply data-centric approaches such as data augmentation, synthetic data generation, curriculum learning, and self-training.
Collaborate with perception, planning, simulation, systems, and software engineering teams.
Drive innovation through new algorithms, technical leadership, publications, and patent generation.
Contribute to production deployment and optimization of machine learning models on automotive platforms.

Requirements

PhD in Computer Science, Engineering, Information Systems, or related field.
Or Master’s degree in a related field with 1+ year of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
Or Bachelor’s degree in a related field with 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
Master’s or Ph.D. training in Computer Science, Electrical Engineering, Robotics, Machine Learning, Artificial Intelligence, or a related field.
5+ years of industry or research experience in machine learning, deep learning, computer vision, robotics, or autonomous driving.
Strong programming skills in Python, PyTorch, and C++ (preferred).
Deep understanding of deep learning and related areas including neural network design, computer vision, Transformers, representation learning, and multimodal learning.
Experience training and evaluating large-scale deep learning models.
Experience building end-to-end ML workflows from data ingestion through deployment.
Strong software engineering fundamentals, including code quality, version control, testing, and reproducible experimentation.
Experience in autonomous driving, ADAS, robotics, or embodied AI.
Experience with end-to-end planners and AI planning systems.
Experience with trajectory prediction, motion planning, or behavior modeling.
Experience with reinforcement learning, imitation learning, or self-supervised learning.
Experience building simulation and closed-loop evaluation frameworks.
Familiarity with ONNX, TensorRT, distributed training, and model optimization techniques.
Publications at top-tier conferences such as CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, or CoRL.
Experience filing patents or developing novel machine learning technologies.

Technologies

Python
PyTorch
C++
ONNX
TensorRT
Transformers

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18d ago

Lead AI Engineer

Qualified Health PBC Palo Alto, CA

Palo Alto, CA

18d ago

$230k - $350k/yr Full time Agentic Ai Ai Agent Ai Agent Platform

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Job Description

Qualified Health PBC is building agentic AI systems that support its full product portfolio, and you will help set the technical direction for how that work scales. This Lead AI Engineer role is based in Palo Alto, CA (onsite) and comes with a USD 230,000 - 350,000 salary range per year, plus equity packages.

You will partner with founders and engineering leadership to connect AI infrastructure investment to company strategy. The focus is both hands-on and organizational: defining multi-year architecture, establishing standards for LLM evaluation and deployment safety, and mentoring staff-level engineers as the applied AI function grows.

What you’ll do

Define the multi-year technical strategy and architecture for agentic workflow infrastructure across the QH product portfolio, supporting 100+ workflows and growing.
Shape decisions on product direction, build-versus-buy, and platform investment by representing applied AI engineering at cross-functional and leadership levels.
Set org-wide engineering standards for LLM evaluation, deployment, safety, and monitoring, contributing to QH’s broader AI governance approach.
Serve as a technical escalation point for the hardest and highest-ambiguity problems across multiple product lines.
Mentor and develop Staff-level engineers, including support for the technical career ladder for applied AI roles.
Stay ahead of model and tooling changes by evaluating emerging options such as OpenAI, Anthropic, and Mistral, and determining what is worth adopting.

Requirements

Python required with a strong foundation in software engineering and demonstrated experience architecting systems used company-wide.
8+ years building production software, including 4+ years building and scaling AI-powered or LLM-driven applications in production.
Proven track record setting technical direction and standards adopted across multiple teams, not limited to a single product line.
Deep expertise in MLOps, model deployment, and workflow automation at an organizational or platform level.
Ability to operate with full autonomy on ambiguous, high-stakes technical and strategic problems.
Strong influence at the leadership level, including with non-technical stakeholders.

Technologies

Python
LLM
MLOps
OpenAI
Anthropic
Mistral

Benefits

Competitive salaries with equity packages
Robust medical/dental/vision insurance
Flexible working hours
Hybrid work options
Inclusive environment that fosters creativity and innovation
Eligible for equity and benefits

Desirable skills

Bachelor’s degree + 10 years OR Master’s degree + 8 years in Computer Science, Engineering, or related field (or equivalent experience).
Recognized expertise in applied AI or agentic systems (internally or externally), such as talks, publications, open source contributions, or prior platform-level roles.
Experience building AI infrastructure in a regulated or high-stakes domain (healthcare, finance, etc.).
Experience founding or scaling a technical function from the ground up in a startup environment.
Experience mentoring Staff-level engineers and shaping technical career ladders.

1mo ago

Staff Applied AI Engineer

Ivanti Utah, UT

Utah, UT

1mo ago Closed

Full time Agentic Ai Ai Agent Ai Agent Platform

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