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Internship Performance Engine Tuning Jobs in California

Senior AEM Developer

Sunnyvale, CA · On-site

$64 - $84.50/hr

... engine indexing and performance. • Collaborate with UI/UX designers, product owners, and other ... tuning efforts. • Develop automated unit and integration tests. • Stay up-to-date with the ...

... engine indexing and performance. • Collaborate with UI/UX designers, product owners, and other ... tuning efforts. • Develop automated unit and integration tests. • Stay up-to-date with the ...

Platform Intelligence Intern

Foster City, CA · On-site

$5.50K - $7.50K/mo

We seek interns who demonstrate strong academic performance, engagement beyond the classroom ... Predictability Engine - ML-driven forecasting and anomaly detection on key operational metrics ...

Platform Intelligence Intern

Foster City, CA · On-site

$5.50K - $7.50K/mo

We seek interns who demonstrate strong academic performance, engagement beyond the classroom ... Predictability Engine - ML-driven forecasting and anomaly detection on key operational metrics ...

HPC Consultant

Fremont, CA · On-site

$52 - $57/hr

Experience in system-level performance tuning across compute, storage, and network layers ... recruitment engine operating across North America and Asia--ensuring speed, quality, and ...

AI Intern- Summer 2026

San Jose, CA · On-site

$40 - $50/hr

Summer Internship Our Summer Internship is designed for students leading into their final year of ... performance. * LLM & Generative AI Research: Work on transformer models, fine-tuning workflows ...

... Engine service and infrastructure. Responsibilities : • Demonstrate expert-level knowledge of the ... performance tuning. • Maintain an excellent grasp of Unix/Linux operating system internals ...

Sr. Cloud Engineer

Redwood City, CA · On-site

$68.25 - $91.25/hr

... performance tuning, debugging, metrics measurement, security, resilient design and disaster ... show engine innodb status;" and working knowledge of admin tools such as monyog. * The ability to ...

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Internship Performance Engine Tuning information

What are the key skills and qualifications needed to thrive as an Internship Performance Engine Tuning specialist, and why are they important?

To excel in an Internship Performance Engine Tuning role, a solid understanding of automotive engineering principles, engine mechanics, and coursework in mechanical or automotive engineering are essential. Familiarity with engine management software, diagnostic tools, and data logging systems—plus basic programming or calibration tool proficiency—is highly valued. Strong analytical thinking, attention to detail, and effective communication skills help interns collaborate with teams and troubleshoot complex issues. These abilities are critical for optimizing engine performance while ensuring reliability, safety, and regulatory compliance in real-world automotive applications.

What kind of projects or tasks can I expect to work on during an Internship in Performance Engine Tuning?

As an intern in Performance Engine Tuning, you’ll typically assist with data collection and analysis from engine tests, help calibrate engine control parameters, and support the team in optimizing engine performance for power, efficiency, or emissions targets. You may also contribute to diagnostic troubleshooting and participate in simulation or dynamometer testing. Collaboration with senior engineers and cross-functional teams is common, offering valuable exposure to both technical and team-based problem-solving.

What are Internship Performance Engine Tuning positions?

Internship Performance Engine Tuning positions are internship roles focused on optimizing and improving engine performance, typically within automotive or motorsports industries. These internships give students or recent graduates hands-on experience with engine calibration, diagnostics, data analysis, and testing. Interns work with experienced engineers to fine-tune engine parameters for increased power, efficiency, and reliability. It's a great way to gain technical skills and industry knowledge, especially for those interested in automotive engineering or high-performance vehicles.

What is the difference between Internship Performance Engine Tuning vs Performance Engine Tuner?

AspectInternship Performance Engine TuningPerformance Engine Tuner
CredentialsTypically pursuing or recent graduate, basic knowledgeRelevant certifications or experience in engine tuning
Work EnvironmentTraining setting, supervised projectsProfessional workshop or automotive shop
Industry UsageEntry-level, learning phaseFull-time, specialized role in automotive industry
Search IntentLearning, entry-level opportunitiesProfessional tuning and performance optimization

Internship Performance Engine Tuning is an entry-level position focused on learning and gaining experience under supervision, while Performance Engine Tuner is a professional role requiring experience and certifications to optimize engine performance in a commercial setting.

What cities in California are hiring for Internship Performance Engine Tuning jobs? Cities in California with the most Internship Performance Engine Tuning job openings:

Forward Deployed Engineer (Inference & Post-Training)

Together AI

San Francisco, CA • On-site, Remote

$270K - $300K/yr

Other

Medical

Posted 23 days ago


Job description

About the role

As a Forward Deployed Engineer (FDE) focused on Inference & Post-Training, you will be a hands-on technical partner to our most strategic customers - production AI teams looking to leverage high quality models and do inference at scale. For us, FDE is not a replacement for a Solutions Architect; you will partner with our SAs as a deep-domain specialist in inference optimization, fine-tuning pipelines, and production deployment. As key contributors to both the CX, Engineering, and Sales organizations, FDEs add tremendous value by ensuring we can meet the requirements of our most complex POCs, facilitate successful platform adoption, and guide tailored optimization efforts - directly impacting customer success, company growth, and the hardening of our core platform.

Responsibilities
  • Inference Engine Optimization: Select, configure, and optimize inference engine based on hardware, model architecture, and workload profile
  • Configuration & Performance Tuning: Develop configuration updates to win critical POCs, benchmarks, and optimize customer deployments; tune KV cache, apply speculative decoding, determine optimal tensor parallelism, and determine quantization strategy to hit throughput and latency targets.
  • Post-Training & Fine-Tuning: Drive hands-on RL training runs and optimize system design; guide customers through LoRA, SFT, DPO, RLHF, and GRPO pipelines from experimentation through production.
  • Strategic Customer Alignment: Act as the primary technical point of contact for aligned strategic accounts - monitoring and optimizing endpoint configurations, helping customers get the most out of the platform, and collaborating to ensure we hit critical milestones.
  • Opinionated Onboarding: Establish direct alignment with strategic customers at onboarding; ensure the right inference and post-training configurations are in place from day one to improve time-to-value.
  • Product Feedback Loop: Directly influence our software and model roadmap by surfacing insights from the field. Contribute back to the product where needed to support customer requirements or drive a better experience. Drive early feature and research adoption with strategic logos.
Qualifications
  • Experience: 5+ years in a technical role, with a strong focus on inference systems, open-source LLM deployment, or post-training workflows.
  • Inference Engine Depth: Expert-level, hands-on experience with inference engines (e.g., vLLM, TensorRT-LLM, SGLang); ability to diagnose and resolve performance issues at the engine level.
  • Inference Optimization: Deep knowledge of KV cache tuning, speculative decoding, tensor parallelism, pipeline parallelism, and quantization techniques
  • Post-Training Knowledge: Hands-on experience with fine-tuning and post-training pipelines, including LoRA, SFT, DPO, RLHF, and GRPO; ability to advise on system design
  • Model Landscape Awareness: Broad knowledge of state-of-the-art open-source models and strong judgment on model selection for specific customer use cases, hardware profiles, and performance targets.
  • Coding Proficiency: Strong Python skills; comfortable working in production environments
About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancements such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers on our journey in building the next generation of AI infrastructure. 

Compensation

We offer competitive compensation, startup equity, health insurance, and other benefits, as well as flexibility in terms of remote work. The US base salary range for this full-time position is: $270,000 - $300,000 OTE + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge. 

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our Privacy Policy at https://www.together.ai/privacy