Santa Clara, CA

Engineer Jobs in Santa Clara, CA

22 jobs found

Include remote jobs

Today

Senior Product Security Engineer

Hologic Santa Clara, CA 🇺🇸 Remote

Santa Clara, CA

Today

$107k - $172k/yr Full time Senior Application Security Cloud Platforms

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Job Description

The Senior Product Security Engineer at Hologic drives Secure by Design across product teams, performs security assessments and risk management, and supports DevSecOps for healthcare solutions. The role may be remote or based in Newark, DE; Santa Clara, CA; Marlborough, MA, or other locations, with a annual salary range of USD 106,600 to 171,800.

Responsibilities

Promote a Secure by Design culture across product teams, ensuring adherence to security standards and best practices.
Help refine and extend Secure by Design policies and procedures to align products with current security requirements and regulatory standards.
Assist in creating and maintaining security design documentation and architecture diagrams.
Perform and document ongoing security assessments, including threat modeling, for Hologic products and remote connectivity solutions; provide guidance to product teams as needed.
Lead Security Risk Management activities to address identified vulnerabilities and security design issues.
Define and maintain security controls and requirements while actively participating in design discussions and activities.
Support product development with Security Code Reviews to ensure alignment with Secure by Design principles and appropriate security controls.
Help automate security testing and reporting, manage security tooling, and secure cloud environments.
Oversee ongoing security monitoring of in-market products and connected health solutions; participate in incident response investigations as necessary.
Educate sales and service teams on securing our products, connected health solutions, and operating environments.

Requirements

Master’s or Bachelor’s degree in Computer Science, Management Information Science, Engineering, or a related technical field.
4+ years of relevant experience in computer and network security, cloud-based platforms, computer networking administration, Windows and Linux operating systems, software application testing and maintenance, and cybersecurity risk assessment.
Knowledge of secure development lifecycle and experience within a development environment.
Expertise in secure application design and code reviews, with understanding of Secure Coding standards and common vulnerabilities (OWASP Top 10, CWEs).
Proficiency in scripting and basic application development (PowerShell, Python, C#, C++).
Experience with industry-standard security tools (SAST, SCA, DAST, vulnerability scanning).
Leadership in Threat Modeling, with STRIDE method preferred.
Penetration testing experience (direct or supportive).
Experience securing development and cloud environments (Azure preferred) and in DevSecOps pipelines (CI/CD).
Strong verbal and written communication skills.

Technologies

PowerShell, Python, C#, C++
Windows, Linux
SAST, SCA, DAST, vulnerability scanning
Azure, STRIDE, Threat Modeling
OWASP Top 10, CWEs
CI/CD

Benefits

Competitive salary and annual bonus scheme
Comprehensive training and continued development
Equal Opportunity Employer

Ideal Candidate Profile

Industry Awareness: Maintains vigilance on industry security threats, assesses risks to Hologic products, and manages these risks per quality procedures.
Troubleshooting Expertise: Diagnoses and resolves issues related to networked, computer-based products.
Travel Flexibility: Available for travel to Hologic offices, training, and customer sites.
Autonomous Alignment: Works with some supervision while aligning with strategic intentions and corporate priorities.
Cloud Knowledge: Strong understanding of cloud design concepts and familiarity with security analysis and protection tools.

Preferred Qualifications

Medical Systems Knowledge: Experience with medical information system administration and familiarity with medical device security standards and regulations (FDA Premarket Cybersecurity Guidance, IEC 81001-5-1, AAMI TIR57, AAMI SW96).
Regulated Industry Experience: Experience in software development and verification within a regulated industry.
Technical Support Experience: Experience providing technical support to field service teams and end-users.
Certifications: Security-related certifications (eg CISSP), OS (Windows, Linux), and networking (Cisco) certifications are strongly preferred.

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3d ago

Supply Chain Data Engineer

NVIDIA Santa Clara, CA

Santa Clara, CA

3d ago

$152k - $288k/yr Full time Apache Airflow Automation Big Data

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Job Description

Join NVIDIA in Santa Clara as a hands-on Supply Chain Data Engineer. This onsite role offers a competitive compensation range of USD 152,000 – 287,500 per year plus equity, and the opportunity to shape planning decisions at the intersection of forecasting and procurement. You will report to executive leadership and collaborate with modeling, procurement, operations, and IT teams to turn data into strategic action. Expect a role that values practical data engineering, strong data governance, and cross-functional partnership in a fast-paced, high-impact environment.

Benefits

Equity

Responsibilities

Design, implement, and scale automated data pipelines using SQL and Python to extract, transform, and load large supply chain datasets from internal and external systems.
Guard data quality as the primary custodian by building automated validation scripts to catch anomalies, missing inputs, and historical mismatches before data enters planning frameworks.
Develop and improve automated pipelines feeding downstream machine learning and AI models, ensuring data is clean, low-latency, and ready for advanced computation.
Architect and maintain highly optimized data tables, views, and schemas tailored for rapid querying by unified computational systems.
Collaborate to deconstruct legacy, decentralized planning workflows and migrate them to automated, centralized data environments that link forecasting to procurement.
Work cross-functionally with engineering, global procurement, operations, and IT to uncover hidden data sources and standardize core supply chain metrics.

Requirements

Bachelor’s degree in Computer Science, Data Engineering, Information Systems, Industrial Engineering, Operations Research, or equivalent experience.
Expert data engineering skills with mastery of SQL and Python, including data manipulation with Pandas.
7+ years of data pipeline experience, with a proven track record of building and operating automated ETL/ELT pipelines in production.
Deep experience with relational databases, data warehouses (Snowflake, BigQuery), or large ERP systems (SAP or Oracle).
Extreme attention to detail and a strong focus on data integrity; you proactively identify and fix issues in large datasets.
High autonomy and comfort starting from loose guidelines to deliver robust, production-ready data pipelines from scratch.

Technologies

SQL
Python
Pandas
Snowflake
BigQuery
SAP
Oracle
Apache Airflow
dbt
AWS
Azure
GCP
MATLAB

Ways to stand out from the crowd

Prior experience building data infrastructure within the semiconductor, electronics, or large-scale technology hardware supply chains.
Background with mathematical modeling environments, advanced computation engines, or algorithmic simulation software such as MATLAB or advanced Python packages.
Familiarity with workflow orchestration tools like Apache Airflow or dbt, or infrastructure used to support Machine Learning pipelines (DataOps).
Experience cloud-architecting supply chain master data on AWS, Azure, or GCP.

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7d ago

Applied Machine Learning Engineer, Circuit Design - New College Grad 2026

NVIDIA Santa Clara, CA

Santa Clara, CA

7d ago

$116k - $219k/yr Full time Electrical Engineering Ai Assisted Engineering Artificial Intelligence

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Job Description

Applied machine learning for circuit design automation at NVIDIA, combining AI driven models with agent based workflows to accelerate end-to-end design tasks across pre-silicon and post-silicon data in a hybrid Santa Clara, CA setting.

Responsibilities

Collaborate within a cross-functional team on projects that leverage pre-silicon and post-silicon hardware design data, focusing on circuit optimization, SPICE correlation, and AI enabled design automation.
Contribute to applications spanning silicon data analysis, manufacturing variation analysis, VLSI circuit design and timing, along with agent driven design exploration and optimization of agent workflows.
Translate stakeholder requirements into data science, AI/ML, and agent based system problems; design and implement end-to-end solutions.
Develop, validate, and deploy models and AI systems that integrate with existing machine learning, design automation, and visualization tools used internally.
Examine datasets to form hypotheses, extract relevant features, and build models along with self improving workflows that operate on top of the data.
Refine models, algorithms, and autonomous optimization loops until performance meets the targeted QOR.

Requirements

Master's or PhD in Electrical or Computer Engineering, Computer Science, or Applied Mathematics, or equivalent practical experience.
Solid knowledge of circuit design, VLSI, ASIC, EDA, silicon analysis, or custom circuit design.
Proven experience in applied math, ML, or software development with a track record of Python and C++ coding.

Technologies

Python
C++
PyTorch
LangChain
LangGraph
SPICE

Benefits

Equity
Benefits

Ways to Stand Out From the Crowd

Experience building AI systems for EDA, design automation, or circuit design workflows.
Research or project experience in AI driven EDA, circuit optimization, design space exploration, or autonomous design systems.
Experience constructing agent based systems, autonomous optimization loops, self improving AI systems, or production scale AI/ML platforms.
Background with deep learning methods and AI agent frameworks, and familiarity with PyTorch, LangChain, or LangGraph is a plus.

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7d ago

Analytics Engineer - AI Trainer

DataAnnotation Santa Clara, CA 🇺🇸 Remote

Santa Clara, CA

7d ago

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

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Job Description

The Analytics Engineer - AI Trainer is a contract role focused on aiding the development of AI systems by evaluating quantitative outputs, solving technical problems, and delivering actionable feedback to enhance AI reasoning. The position supports remote work with flexible scheduling.

Responsibilities

Evaluate AI-generated quantitative work, including statistical analysis, predictive modeling, scientific reasoning, and data-driven insights, for technical accuracy and real-world validity.
Design and solve quantitative problems used to train and benchmark AI systems, spanning forecasting, experimental analysis, optimization, and statistical inference.
Write clear technical explanations and well-documented analytical code.
Provide feedback that directly shapes the next generation of AI models built for quantitative reasoning.

Requirements

3+ years of hands-on experience in a quantitative role or research environment, such as data science, statistics, economics, finance, physics, biology, epidemiology, operations research, or related fields.
Some coding experience, comfortable writing and reviewing analytical code end-to-end.
Practical experience with statistical methods, predictive modeling, and experiment design (A/B testing, hypothesis testing, regression, classification, time-series forecasting).
Fluency in English with strong writing skills.
Bachelor's degree in a quantitative field preferred; advanced degrees (Master's or PhD) are a plus.
Relevant credentials are a plus (e.g., Kaggle competition ranking, AWS or GCP ML certifications, or equivalent demonstrated expertise).

Location and Employment Details

Location: Santa Clara, CA, with remote work options.

Employment type: Contract

Compensation: USD 50 - 100 per hour

Benefits

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

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9d ago

Senior Machine Learning Engineer

NVIDIA Santa Clara, CA

Santa Clara, CA

9d ago

$184k - $357k/yr Full time Senior Artificial Intelligence Autonomous Vehicles

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Job Description

NVIDIA offers an onsite opportunity in Santa Clara, CA to help build the machine learning backbone for DRIVE AV perception. The role sits at the intersection of LiDAR and camera perception, data pipelines, and production-ready C++ code, with a competitive salary range of USD 184,000 to 356,500 per year, plus equity and comprehensive benefits. You will collaborate with LiDAR and camera teams to deliver reliable autonomous driving solutions and advance perception technology in a production environment.

Responsibilities

Model Development: Design, train, and optimize innovative ML models for LiDAR perception, including road element detection, semantic segmentation, and tracking.
End-to-end ML workflows: Develop and coordinate data pipelines, model training, metrics, continuous performance instrumentation, and reporting.
Productization: Transition ML models from evaluation to shipping as part of the NVIDIA DRIVE AV platform, writing highly efficient production code in C++.
Innovation: Stay current with ML advancements and integrate techniques that boost platform performance.
Collaboration: Work with LiDAR and camera teams, developers, engineers, and managers to turn complex ideas into reliable autonomous driving solutions.

Requirements

BS or MS in Computer Science, Engineering, or a related field, or equivalent experience.
6+ years of relevant industry experience applying machine learning to real-world problems.
Strong C++ and Python programming and debugging skills for large, complex systems.
Deep practical experience applying ML to LiDAR/camera perception in automotive or related fields.
Experience with deep learning frameworks such as PyTorch and TensorFlow, with solid understanding of ML fundamentals.
Experience building and sustaining training and essential metric workflows for large-scale datasets.
Excellent communication and analytical skills, with self-motivated drive to solve hard problems.

Technologies

C++, Python
PyTorch
TensorFlow
TensorRT

Benefits

Equity
Benefits

Ways to stand out from the crowd

LiDAR or Camera Perception Experience: Proven track record of developing and shipping deep learning models for LiDAR/Camera in a production environment.
Advanced Model Knowledge: Familiarity with modern architectures such as Transformers and their application to visual recognition tasks.
AV Production Experience: History of delivering ML features and models into a production autonomous vehicle stack or robotics product.
Performance Optimization: Experience with model optimization for real-time inference on embedded or automotive platforms, including TensorRT.

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10d ago

Principal Machine Learning Engineer, Accelerated Apache Spark

NVIDIA Santa Clara, CA

Santa Clara, CA

10d ago

$272k - $431k/yr Full time Python Big Data Bigdata

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Job Description

Responsibilities

Design and implement ML solutions to predict performance and optimize GPU-accelerated Spark workloads in enterprise environments.
Develop cutting-edge algorithms and adaptive frameworks to continually enhance Spark performance on GPUs.
Build AI-driven agents and tooling to diagnose system issues and optimize applications.
Collaborate with strategic partners and customers to deploy sophisticated ML solutions across diverse environments.
Maintain up-to-date domain expertise by tracking the latest advances in ML systems and algorithms.
Provide technical mentorship and leadership in data science and ML to a team of engineers.

Requirements

BS, MS, or PhD, or equivalent experience in Machine Learning, Data Science, Computer Science, or a closely related field.
12+ years designing, implementing, and deploying high-quality ML/DL solutions.
At least 5 years in a technical lead role overseeing ML model development.
2+ years hands-on experience with large-scale data processing platforms such as Apache Spark.
Proven ability to apply modern tooling and best practices across the ML model lifecycle.
Strong Python programming skills and experience with numpy, pandas, scikit-learn, scipy, PyTorch, and TensorFlow.
Extensive experience with advanced ML approaches, including LLM/GenAI, reinforcement learning, and adaptive online ML systems.
Deep expertise in feature engineering, assessing feature importance, and building boosted tree models such as XGBoost.

Technologies

Python
numpy
pandas
scikit-learn
scipy
pytorch
tensorflow
Apache Spark
XGBoost
Scala
Java
C++
CUDA

Benefits

Equity and comprehensive benefits

Ways to stand out

Understanding of the internal workings and architecture related to Apache Spark
Familiarity with NVIDIA GPUs and CUDA
Experience coding in Scala, Java, and/or C++

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10d ago

Senior Machine Learning Engineer, End‑to‑End Autonomous Driving

NVIDIA Santa Clara, CA

Santa Clara, CA

10d ago

$184k - $357k/yr Full time Senior Active Learning Artificial Intelligence

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Job Description

NVIDIA in Santa Clara, CA is seeking a Senior Machine Learning Engineer to design, train, and deploy end-to-end autonomous driving models while building data-centric pipelines and data flywheels that accelerate learning from real-world data. This onsite role involves close collaboration across researchers and engineers to translate cutting-edge research into robust, production-ready ML systems for autonomous driving. The position offers a salary range of USD 184,000 to 356,500 per year and targets candidates with advanced degrees and substantial experience in modern deep learning and data-centric methods.

Responsibilities

Designing, implementing, and training large-scale end-to-end driving models.
Driving the data flywheel: identifying failure cases, specifying data collection and labeling needs, and iterating models to close real-world performance gaps.
Building, curating, and maintaining high-quality multimodal datasets (e.g., video, sensor, language/action traces) tailored for end-to-end autonomous driving.
Developing and applying data-centric learning algorithms such as active learning, curriculum learning, automated hard-example mining, outlier and novelty detection, and semi/self-supervised methods.
Exploring and productizing new data sources including simulation, synthetic data, and world-model-based generation/augmentation to improve coverage and robustness.
Designing and implementing agentic data workflows that automate data discovery, labeling, evaluation, and retraining to maximize development velocity.
Fostering collaborative partnerships with researchers and engineers, transforming innovative research into robust, industrial-strength machine learning models.

Requirements

A PhD with 4+ years, an MS with 6+ years, or a BS (or equivalent experience) with 8+ years of relevant experience in Computer Science, Computer Engineering, or a related technical field.
Strong background in modern deep learning, including transformer-based architectures, video modeling, and multimodal VLM/VLA or foundation models.
Hands-on experience training and deploying deep learning models on real-world datasets: data preprocessing, distributed training, evaluation, debugging, and iterative improvement.
Practical experience with data-centric methods such as active learning, curriculum learning, outlier/novelty detection, or large-scale sample mining.
Proficiency in Python and at least one major deep learning framework (PyTorch, TensorFlow, or JAX), plus solid software engineering practices (testing, code review, CI/CD).
Demonstrated ability to collaborate across teams, drive designs from prototype to production, and communicate clearly with technical and non-technical partners.
Track record of leading complex cross-team projects, setting technical direction, and making critical technical decisions that impact multiple teams or products.

Technologies

Python
PyTorch
TensorFlow
JAX

Benefits

Equity
Benefits

Ways to stand out from the crowd

Experience building and operating data flywheels or large-scale data pipelines for ML, including data quality monitoring and continuous retraining loops.
Direct experience with end-to-end driving models, large-scale behavior cloning, or reinforcement/imitation learning for driving or robotics.
Experience leveraging simulation, synthetic data, or world models to generate training and evaluation data for autonomous systems.
Contributions to sophisticated methods in data-centric ML, VLM/VLA, or autonomous driving, such as impactful publications, open-source projects, or widely used internal tools.
Background with safety, reliability, and validation requirements for autonomous driving or other safety-critical applications.