Santa Clara, CA

Developer Jobs in Santa Clara, CA

11 jobs found

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Today

Senior Machine Learning Engineer

NVIDIA Santa Clara, CA

Santa Clara, CA

Today

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

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Job Description

NVIDIA seeks a Senior Machine Learning Engineer in Santa Clara, CA (onsite) to build the ML backbone of the DRIVE AV perception stack, focusing on LiDAR and camera perception, data pipelines, and production-grade C++ implementations, with a salary range of USD 184,000 - 356,500 per year.

Responsibilities

Model development: design, train, and optimize cutting edge ML models for LiDAR perception such as road element detection, semantic segmentation, and tracking.
ML workflow orchestration: own end to end pipelines including data ingestion, model training, metrics tracking, continuous performance instrumentation, and reporting.
Productization: translate experimental models into shipped components of the NVIDIA DRIVE AV platform, delivering efficient production code in C++.
Innovation: monitor recent advances in machine learning and apply techniques that boost platform performance.
Cross functional collaboration: work with LiDAR and camera teams, software engineers, and project managers to convert complex ideas into reliable autonomous driving solutions.

Requirements

A BS or MS in Computer Science, Engineering, or a related field, or equivalent experience.
At least 6 years of industry experience applying machine learning to real world problems.
Strong C++ and Python programming and debugging skills, with experience building for large, complex systems.
Hands on practical experience applying ML to LiDAR and camera perception in automotive or related domains.
Experience with deep learning frameworks such as PyTorch or TensorFlow, plus solid grounding in the mathematical foundations of ML.
Experience building and maintaining training and metrics workflows for large scale datasets.
Excellent communication and analytical abilities; self motivated to solve challenging problems.

Technologies

C++
Python
PyTorch
TensorFlow
TensorRT

Benefits

Equity
Benefits

Ways to Stand Out

LiDAR or Camera Perception Experience: proven track record shipping deep learning models for LiDAR/Camera in production environments.
Advanced Model Knowledge: familiarity with modern architectures such as Transformers and their use in visual recognition tasks.
AV Production Experience: history delivering ML features and models into production autonomous vehicle stacks or related robotics products.
Performance Optimization: experience optimizing models for real time inference on embedded or automotive platforms, including TensorRT.

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1d ago

Principal Machine Learning Engineer, Accelerated Apache Spark

NVIDIA Santa Clara, CA

Santa Clara, CA

1d ago

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

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Job Description

NVIDIA offers equity and a benefits package, with an on-site机会 in Santa Clara, CA. This Principal Machine Learning Engineer role sits on the Accelerated Apache Spark team, focusing on ML driven performance prediction and optimization for GPU-accelerated Spark workloads. You will lead ML engineering efforts, mentor engineers, and help deploy AI based tooling across multiple environments, all within a culture that values technical excellence and collaboration. The position carries a salary range of USD 272,000 to 431,250 per year and requires onsite presence.

Responsibilities

Design and implement machine learning solutions for predicting and optimizing performance of GPU-accelerated enterprise Apache Spark workloads.
Develop advanced algorithms and adaptive systems to continually improve Spark performance on GPUs.
Build AI based agents and tools to assist with diagnosing issues and optimizing applications.
Partner with key stakeholders and customers to deploy complex ML solutions across diverse environments.
Maintain deep domain expertise by tracking the latest advances in ML systems and algorithms.
Provide technical mentorship and leadership in data science and machine learning for 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 of professional experience designing, implementing, and productionizing high quality ML/DL solutions.
5+ years as a technical lead in ML model development.
Proven hands-on experience (2+ years) with large-scale data processing platforms such as Apache Spark.
Proven ability to employ modern tooling and sound techniques for crafting, deploying, and maintaining ML models.
Excellent programming skills in Python and related data science libraries (numpy, pandas, scikit-learn, scipy, pytorch, tensorflow).
Deep experience with ML methodologies including LLM/GenAI, reinforcement learning, and adaptive online ML systems.
Strong expertise in feature engineering, feature importance assessment, and developing boosted tree models (e.g., XGBoost).

Technologies

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

Benefits

Equity and 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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1d ago

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

NVIDIA Santa Clara, CA

Santa Clara, CA

1d ago

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

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Job Description

Join NVIDIA in Santa Clara, onsite, to lead the design, training, and deployment of end-to-end autonomous driving models. This senior role offers a salary range of USD 184,000 to 356,500 per year, plus equity and a comprehensive benefits package. You will collaborate across teams to build data-centric pipelines, drive data flywheels, and translate research into robust, production-grade machine learning systems for autonomous driving.

Benefits

Equity
Benefits

Responsibilities

Design, implement, and train large-scale end-to-end driving models.
Lead the data flywheel by identifying failure cases, specifying data collection and labeling needs, and iterating models to close real-world gaps in performance.
Build, curate, and maintain high-quality multimodal datasets (video, sensor, language/action traces) tailored for end-to-end autonomous driving.
Apply data-centric learning methods such as active learning, curriculum learning, automated hard-example mining, outlier and novelty detection, and semi/self-supervised approaches.
Explore and productize new data sources including simulation, synthetic data, and world-model based generation to improve coverage and robustness.
Design data workflows that automate data discovery, labeling, evaluation, and retraining to maximize development velocity.
Foster collaborative partnerships with researchers and engineers to transform innovative research into robust, industrial-strength models.

Requirements

PhD with 4+ years, MS with 6+ years, or BS (or equivalent experience) with 8+ years of relevant work 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), along with solid software engineering practices (testing, code review, CI/CD).
Proven ability to collaborate across teams, drive designs from prototype to production, and communicate clearly with technical and non-technical partners.
A track record of leading complex cross-team projects, setting technical direction, and making critical decisions that impact multiple teams or products.

Technologies

Python
PyTorch
TensorFlow
JAX

Ways to stand out

Experience building and operating data flywheels or large-scale ML data pipelines, 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 advanced data-centric ML methods, VLM/VLA, or autonomous driving through publications, open-source projects, or widely used internal tools.
Background with safety, reliability, and validation requirements for autonomous driving or other safety-critical applications.

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2d ago

Senior Applied Machine Learning Engineer - VLSI Design

NVIDIA Santa Clara, CA

Santa Clara, CA

2d ago

$152k - $265k/yr Full time Senior Agent Based Design Analytics

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Job Description

NVIDIA in Santa Clara, California is seeking a Senior Applied Machine Learning Engineer focused on VLSI design automation. This role blends data science, AI systems, and agentic approaches to accelerate both pre-silicon and post-silicon hardware design and circuit optimization, with integration into existing tools in the EDA ecosystem. The position offers a hybrid work arrangement and a salary range of USD 152,000 to 264,500 per year. A minimum of four years of relevant experience and an MS or PhD in Electrical/Computer Engineering, Computer Science, or Applied Mathematics are expected.

Responsibilities

Collaborate within a cross-functional team on projects involving pre-silicon and post-silicon hardware design data, circuit optimization, SPICE correlation, and AI-driven design automation workflows.
Contribute to applications spanning silicon data analysis, manufacturing process variation analysis, VLSI circuit design, timing, and agent-driven design exploration and flow optimization.
Translate requirements into data science, ML, and agent-based system problems; architect and implement solutions.
Test and deploy models and AI systems that integrate with existing machine learning, design automation, and visualization tools within the organization.
Analyze datasets, formulate and validate hypotheses, extract relevant features, and build models plus self-improving workflows on top of them.
Refine models, algorithms, and autonomous optimization systems until the desired QOR is reached.

Requirements

MS/PhD in Electrical/Computer Engineering, Computer Science, Applied Mathematics, or equivalent experience.
4+ years of experience in circuit design, VLSI, ASIC, EDA, silicon analysis, or custom circuit design.
Demonstrated ability in Python and C++ with a background in applied mathematics, ML, or software development.
Experience with deep learning algorithms and AI agent frameworks; familiarity with PyTorch, LangChain, or LangGraph is a plus.

Technologies

Python
C++
PyTorch
LangChain
LangGraph

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 work in AI-driven EDA, circuit optimization, design-space exploration, or autonomous design systems.
Experience developing agentic systems, autonomous optimization loops, self-improving AI systems, or production-scale AI/ML platforms.
Strong verbal and written communication skills and the ability to present technical content effectively.
Self-motivated with a passion for growth, continuous learning, and sharing findings with the team.

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3d ago

Senior Software Engineer - Topography

NVIDIA Santa Clara, CA 🇺🇸 Remote

Santa Clara, CA

3d ago

$184k - $288k/yr Full time Backend Developer Senior Cloud

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Job Description

NVIDIA seeks a Senior Software Engineer to contribute to a Kubernetes native topology platform that gathers, standardizes, and exposes topology data for provisioning systems and workload schedulers across multiple cloud providers, with collaboration on NVIDIA hardware to optimize GPU to GPU scheduling.

Role Details

Location: Santa Clara, CA (remote). Salary: USD 184,000 - 287,500 per year. Minimum experience: 8 years. Education: Bachelor’s degree.

Responsibilities

Develop a system that collects topology information from multiple sources.
Aggregate and normalize collected data to support provisioning systems and workload schedulers.
Contribute directly to the open source project Topograph.
Collaborate with cutting edge hardware to ensure efficient scheduling for new product launches.

Requirements

Minimum of 8 years of relevant experience.
Bachelor’s degree in Computer Science, Software Engineering, Computer Engineering, or a related technical field, or equivalent experience.
Strong production engineering experience in Go or another systems language.
Experience with distributed systems, Kubernetes, Slurm/Slinky, Linux, containers, APIs, and CI.
Ability to design clean interfaces between discovery logic, data models, and scheduler output.
Familiarity with networking, cluster topology, cloud infrastructure, or large-scale compute systems.
Excellent testing, debugging, documentation, and code review habits.

Technologies

Go
Kubernetes
Slurm
Slinky
Kueue
DRA
Topograph

Benefits

Equity
Benefits

Ways to Stand Out From the Crowd

Experience with GPU clusters, NVLink, InfiniBand, Ethernet fabrics, or HPC.
Hands-on work with Kubernetes scheduling, Slurm/Slinky topology, DRA, Kueue, Slinky, or device plugins.
Experience integrating with cloud provider topology APIs or cluster metadata systems.

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3d ago

Senior Data Engineer, Engineering Data Analytics

NVIDIA Santa Clara, CA

Santa Clara, CA

3d ago

$168k - $270k/yr Full time Senior Analytics Big Data

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Job Description

Based in Santa Clara, CA onsite, NVIDIA seeks a Senior Data Engineer to design and scale cloud-based data platforms and analytics for engineering data analytics, focusing on data models, pipelines, and AI enabled insights.

Responsibilities

Build and evolve trusted engineering analytics datasets, data models, and data products for semiconductor product, manufacturing, and test data.
Translate complex domain concepts into reliable data structures, metric logic, validation rules, and reusable analytics layers.
Own and improve curated data layers, including prep/fact tables, silver/gold datasets, semantic views, and analytics-ready outputs.
Partner with product engineering, UI, and data engineering teams to turn ambiguous engineering questions into scalable data solutions.
Define data quality checks, acceptance criteria, and validation frameworks for production analytics data.
Provide technical direction by defining standards, reviewing designs, and ensuring long-term maintainability.
Help guide the evolution of data architecture across modern warehouse, data lake, and lakehouse technologies such as Redshift, S3/Athena, and Databricks.
Support AI-enabled analytics by building well-governed, semantically clear datasets for AI-based exploration, anomaly detection, prediction, and recommendations.
Optimize data pipelines and analytics datasets for correctness, performance, scalability, reliability, and cost.

Requirements

Strong SQL skills, including advanced concepts such as window functions, CTEs, complex joins, aggregation patterns, query optimization, and analytical query design.
Strong Python skills, or equivalent experience building data-intensive software systems.
Experience designing data models, analytics datasets, data products, or application data layers.
Experience building or owning production data pipelines, data platforms, or analytics systems.
Solid understanding of data correctness, table grain, lineage, metric definitions, validation rules, and data quality standards.
Ability to learn complex technical domains and identify when data outputs are technically valid but semantically wrong.
Ability to work cross-functionally with domain experts, engineers, product/UI teams, and data engineering teams while providing technical ownership and judgment.
Interest in applied AI/ML and how trusted data foundations enable AI-based exploration, anomaly detection, predictive analytics, and recommendations.
Bachelor’s or Master’s degree in Computer Science or Computer Engineering or Electrical Engineering (or equivalent experience) and 8+ years of relevant experience.

Technologies

Python, SQL, Redshift, S3, Athena, Glue, EMR, Spark, Databricks, Delta Lake

Benefits

Equity
Benefits

Ways to Stand Out

Experience with semiconductor product engineering, test engineering, yield analytics, manufacturing analytics, quality, reliability, or hardware engineering data is a strong plus.
Experience with modern cloud data platforms and lakehouse technologies such as S3, Athena, Glue, Redshift, EMR, Spark, Databricks, Delta Lake, or similar technologies.
Experience with AI/ML enabled analytics, including LLMs, RAG, AI-based data exploration, natural-language-to-SQL, feature engineering, anomaly detection, prediction, or recommendation systems.
Experience building engineering analytics platforms, internal data products, or decision-support tools for technical users.

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4d ago

AI Data Engineer – Platform & Analytics

Advanced Micro Devices, Inc Santa Clara, CA

Santa Clara, CA

4d ago

Full time Analytics Apache Airflow Artificial Intelligence

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Job Description

AMD seeks an AI Data Engineer to design a medallion data lakehouse and end-to-end pipelines for manufacturing, IoT, and yield analysis data, leveraging AI tooling to accelerate development across multiple engines.

Responsibilities

Architect and maintain a scalable medallion data lakehouse structure with Bronze, Silver, and Gold layers using Apache Iceberg.
Construct and optimize curated Gold-layer data products for high‑performance consumption across an open ecosystem of engines including Snowflake, Databricks (Spark), Trino/Starburst, AWS Athena, and Presto.
Design, develop, and manage complex, resilient data workflows and DAGs with Apache Airflow.
Build, deploy, and monitor end-to-end ETL/ELT pipelines to ingest diverse semiconductor data streams into the data lake.
Model data to enable high‑performance consumption, delivering clean, transformed, production‑ready datasets.
Write and tune highly optimized SQL queries for transformation, analysis, and performance benchmarking.
Leverage generative AI coding assistants and automation tools to speed up pipeline development, documentation, and testing.
Implement data governance practices, data quality checks, and schema evolution rules within Iceberg and Snowflake environments.

Requirements

Demonstrated experience in software, data engineering, and data management.
Hands-on expertise scheduling and monitoring production-grade pipelines with Apache Airflow.
Proven ability to design medallion architectures and extensive experience with Apache Iceberg.
Advanced proficiency with Snowflake and hands-on experience building transformation models in DBT Core.
Expert level SQL and Python knowledge with mastery of modern ETL/ELT patterns and design principles.
Ability to write high quality code with keen attention to detail.
Experience with modern concurrent programming and threading APIs.
Experience with software development processes and tools such as debuggers, GitHub, and profilers is a plus.
Demonstrated use of AI tooling to accelerate development, including GitHub Copilot, Snowflake Cortex, LLM APIs, Claude Code, and related platforms.
Proven track record delivering multiple enterprise-grade, production-level, end-to-end data pipeline solutions from scratch.