ZipRecruiter

Log In

1

Performance Engine Tuning Jobs in California (NOW HIRING)

CYNET SYSTEMS

ML Engineer II

Aliso Viejo, CA · On-site

$52 - $57/hr

Docker, CI/CD, pytest, secure secrets, monitoring, performance tuning. Qualification And Education ... recruitment engine operating across North America and Asia--ensuring speed, quality, and ...

AllSTEM Connections

Data Analyst IV

San Francisco, CA · On-site

$187K - $220K/yr

Hands-on experience with Databricks, PySpark/Python, and at least one high-performance query engine. oVisualization/Governance: Expert-level development and performance tuning in BI platforms (e.g ...

Together AI

Research Engineer, Core ML

San Francisco, CA · On-site

$241K/yr

... performance across GPU, networking, and memory layers to improve latency, throughput, and cost. • ... inference engine, data pipeline, and user‑facing layers. • Run ablations and scale‑up ...

Amplitude

Staff Software Engineer

San Francisco, CA · On-site

Our in-house OLAP engine, Nova , processes trillions of events in real time - turning raw ... Profile and optimize JVM performance: GC tuning, memory management, concurrency, and data layout ...

Cisco

Efficiency AI Ops Engineer Hybrid

San Jose, CA · On-site

$126K - $165K/yr

... AI engine that powers productivity and process automation for all of Cisco. We are a rapidly ... performance. * Where applicable propose and evaluate results of fine-tuning open source LLMs with ...

Cisco

Efficiency AI Ops Engineer Hybrid

San Jose, CA · Hybrid

... AI engine that powers productivity and process automation for all of Cisco. We are a rapidly ... performance. * Where applicable propose and evaluate results of fine-tuning open source LLMs with ...

next page

Showing results 1-20

All JobsPerformance Engine Tuning JobsPerformance Engine Tuning Jobs in California

Performance Engine Tuning information

See California salary details

$108.1K

$123.4K

$137.2K

How much do performance engine tuning jobs pay per year?

As of Jul 14, 2026, the average yearly pay for performance engine tuning in California is $123,363.00, according to ZipRecruiter salary data. Most workers in this role earn between $116,000.00 and $130,800.00 per year, depending on experience, location, and employer.

What does a typical day look like for someone working in Performance Engine Tuning?

A typical day for a Performance Engine Tuning specialist involves assessing customer vehicles, performing engine diagnostics, calibrating ECU settings, and utilizing dynamometer testing equipment to validate performance improvements. You may collaborate closely with other technicians, service advisors, and occasionally directly with clients to discuss performance goals and modifications. The role requires a blend of hands-on adjustments and computer-based tuning, with an emphasis on both technical expertise and precision. Over time, you may also be involved in researching new tuning techniques and staying updated with advancements in automotive technology to ensure optimal results for a wide range of vehicles.

What is a Performance Engine Tuning job?

A Performance Engine Tuning job involves optimizing an engine's performance by adjusting parameters such as fuel injection, ignition timing, and air-to-fuel ratio. Tuners use specialized software and tools to modify the engine control unit (ECU) for better horsepower, torque, and efficiency. This role requires knowledge of engine mechanics, diagnostics, and aftermarket modifications. Tuners work with various vehicles, from daily drivers to high-performance race cars, ensuring they run efficiently and safely.

What are the key skills and qualifications needed to thrive in the Performance Engine Tuning position, and why are they important?

To thrive in Performance Engine Tuning, you need a solid background in automotive mechanics, internal combustion engine theory, and hands-on experience with diagnostic and tuning procedures. Familiarity with engine management systems, ECU programming tools, and performance software (such as Dynojet or HP Tuners) is typically required, along with relevant technical certifications. Strong analytical thinking, attention to detail, and effective communication are valuable soft skills in this field. These competencies are crucial for accurately optimizing engine performance, troubleshooting issues, and conveying technical information to clients or team members.

What job categories do people searching Performance Engine Tuning jobs in California look for? The top searched job categories for Performance Engine Tuning jobs in California are:
Performance Engine Tuning jobs near you
Infographic showing various Performance Engine Tuning job openings in California as of July 2026, with employment types broken down into 90% Full Time, 5% Part Time, 1% Temporary, 3% Contract, and 1% Nights. Highlights an 93% Physical, 1% Hybrid, and 6% Remote job distribution, with an average salary of $123,363 per year, or $59.3 per hour.
Senior Machine Learning Engineer, Voice AI

Senior Machine Learning Engineer, Voice AI

Together AI

San Francisco, CA • On-site

$123K - $169K/yr

Full-time

Re-posted 15 days ago

Job description

Job Summary:
Together AI is building the best inference infrastructure for voice applications, and they are seeking a Senior ML Engineer to drive the model serving layer for voice workloads. This role involves optimizing inference engines and ensuring new model architectures can transition from research to production quickly.
Responsibilities:
• Own the model serving stack that powers Together's voice platform across STT, TTS, and speech-to-speech.
• Work directly with state-of-the-art accelerators (H100s, H200s, B200s) to optimize voice model inference.
• Collaborate with model partners (Cartesia, Deepgram, Rime, and others) to bring their models to production on Together's infrastructure.
• Build quality evaluation frameworks that guide model selection for customers and inform the roadmap.
• Join a small, early-stage team with outsized impact on a fast-growing product area.
• Optimize inference performance for voice models (STT, TTS, speech-to-speech) — targeting best-in-class TTFB, throughput, and GPU utilization across our curated model set.
• Productionize voice models on serverless and dedicated endpoints, including batching strategies, streaming inference, and memory management tailored to audio workloads.
• Build and maintain a voice model evaluation framework — measuring WER across accents, languages, and noise conditions for STT; naturalness, latency, and pronunciation accuracy for TTS.
• Enable new model architectures in our serving stack as the field evolves, including audio-native LLMs, codec-based models (SNAC), and speech-to-speech systems.
• Collaborate with model partners to integrate and optimize their models (Cartesia, Deepgram, Rime, and others) running on Together's infrastructure.
• Profile and debug performance across the full inference stack — from GPU kernels to framework-level bottlenecks — and ship measurable improvements.
• Work with the platform engineering side of the team to ensure the serving layer meets the latency and reliability requirements of real-time voice APIs.
• Contribute to voice model fine-tuning capabilities (STT and TTS) as we enable customers to build differentiated voice experiences on Together.
• Lay the groundwork for multiple new products down the line.
Qualifications:
Required:
• 5+ years of experience in ML engineering, with a focus on model serving, inference optimization, or ML infrastructure.
• Hands-on experience with LLM serving engines (vLLM, SGLang, TensorRT-LLM, or similar) — comfortable reading and modifying engine internals, not just using APIs.
• Strong proficiency in Python and PyTorch; experience with GPU profiling and optimization (CUDA, memory management, kernel-level debugging).
• Track record of shipping ML systems to production with measurable performance improvements.
• Strong product sense — you think about what developers building voice apps actually need, not just what's technically interesting.
• Comfort working on a small, early-stage team where you'll wear multiple hats and move fast.
• Bachelor's or Master's degree in Computer Science, Electrical Engineering, or related field, or equivalent practical experience
Preferred:
• Experience with speech and audio ML (ASR, TTS architectures, audio signal processing) is a strong plus but not required — you can learn this quickly if you have strong ML engineering fundamentals.
• Familiarity with audio codecs and tokenization schemes (SNAC, Encodec, DAC) is a plus.
• Experience training or fine-tuning speech models is a plus.
Company:
Together AI provides a cloud platform for developing, training, fine-tuning, and deploying generative AI models. Founded in 2022, the company is headquartered in San Francisco, USA, with a team of 201-500 employees. The company is currently Growth Stage.

Apply