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Ecs Tuning Jobs in California (NOW HIRING)

Troveo AI Inc

Senior Back End Engineer

San Francisco, CA · On-site +1

$175K - $195K/yr

Work extensively with Elasticsearch - indexing, querying, aggregations, performance tuning, and ... Troubleshoot complex issues across services, ECS and EKS clusters, and Elasticsearch * Improve ...

Apple

Site Reliability Engineer (SRE)

San Diego, CA · On-site

$60.50 - $80.50/hr

... ECS or EKS Ability to write code in one of many high level languages (Python preferred) BS and a ... tuning Last but not least, you are battle-tested and have a few interesting production tales

Fluency

AI Engineer

San Francisco, CA · On-site

$180 - $250/hr

Experience with post-training or fine-tuning. * Experience deploying AI features on AWS Lambda, ECS Fargate, or similar. * Background in ML, NLP, or applied research. * Experience with structured ...

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Ecs Tuning information

What is ECS Tuning?

ECS Tuning is a company that specializes in providing aftermarket and performance parts for European cars, including Audi, BMW, Mercedes-Benz, Mini, Porsche, and Volkswagen. They offer a wide range of products such as replacement parts, performance upgrades, wheels, and accessories. ECS Tuning is known for its extensive online catalog, technical expertise, and commitment to customer service, making it a popular choice among car enthusiasts and mechanics looking to maintain or upgrade their vehicles.

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

To thrive as an ECS Tuning Specialist, you need a strong understanding of automotive systems, mechanical aptitude, and experience with performance parts installation or sales, often supported by technical certifications or automotive training. Familiarity with diagnostic tools, tuning software, and e-commerce platforms is essential for handling both installation and customer support tasks. Attention to detail, customer service skills, and effective communication help build trust with clients and ensure accurate recommendations. These skills are vital for maintaining product quality, delivering excellent service, and supporting customer satisfaction in the specialized automotive aftermarket industry.

What are some of the common challenges faced by team members at ECS Tuning, and how can new hires best prepare for them?

Team members at ECS Tuning often work in a fast-paced environment where they need to stay updated on a wide range of automotive products and evolving customer needs. Common challenges include balancing multiple projects, handling detailed technical inquiries, and collaborating with colleagues across departments like sales, support, and warehouse operations. New hires can best prepare by developing strong communication skills, maintaining a proactive approach to learning about automotive parts, and being adaptable to shifting priorities. Embracing teamwork and staying organized will help you succeed in this dynamic setting.

What is the difference between Ecs Tuning vs Automotive Technician?

AspectEcs TuningAutomotive Technician
CertificationsPerformance tuning certifications, ECU remappingASE certifications, manufacturer-specific training
Work EnvironmentPerformance shops, tuning centersDealerships, repair shops
Industry UsageCar enthusiasts, aftermarket tuningGeneral vehicle maintenance and repair

While Ecs Tuning specializes in ECU remapping and performance upgrades for vehicles, Automotive Technicians focus on diagnosing and repairing a wide range of vehicle issues. Both roles require automotive knowledge, but Ecs Tuning is more niche, targeting performance enhancements, whereas Automotive Technicians work across various vehicle systems in repair settings.

What are popular job titles related to Ecs Tuning jobs in California?

For Ecs Tuning jobs in California, the most frequently searched job titles are:

What job categories do people searching Ecs Tuning jobs in California look for?

The top searched job categories for Ecs Tuning jobs in California are:

Ecs Tuning jobs near you
Infographic showing various Ecs Tuning job openings in California as of August 2026, with employment types broken down into 83% Full Time, 8% Part Time, and 9% Contract. Highlights an 80% Physical, 6% Hybrid, and 14% Remote job distribution.

Staff Machine Learning Engineer

AppFolio, Inc

Santa Barbara, CA • On-site

$200 - $250/hr

Other

Re-posted 7 days ago

AppFolio rating

7.2

Company rating: 7.2 out of 10

Based on 8 frontline employees who took The Breakroom Quiz

184th of 247 rated software companies

Job description

Staff Machine Learning Engineer – Software Engineering

Locations: Santa Barbara, CA; San Diego, CA; Remote - San Francisco, CA; Remote - Denver, CO.

Overview

We’re building an AI‑native platform for the real estate industry and are looking for a Staff Machine Learning Engineer to advance the ML platform that underpins all of AppFolio’s AI initiatives.

Your Impact
  • ML Platform: Design and operate AppFolio’s ML infrastructure on AWS – ECS, SageMaker, GPU fleets, model serving, autoscaling, and cost controls.
  • Drive AI Cost Discipline: Optimize cost across all AI applications – provider routing, caching, batch vs. real‑time, model-size selection, and inference economics.
  • Multi‑Provider Reliability: Maintain reliable, multi‑provider LLM access across Google, OpenAI, and Anthropic with sensible fallbacks and abstractions.
  • Training & Fine‑Tuning Stack: Build the training and fine‑tuning stack for small language models, including data pipelines, GPU orchestration, and evaluation.
  • Productionize Research: Partner with Voice & Agents and Research ML engineers to harden prototypes into production systems with SLOs, on‑call rotations, and observability.
  • AI Safety & Guardrails: Operate AppFolio’s AI safety and authorization layer – guardrails on AWS, scoped tool permissions, and human‑in‑the‑loop gates for autonomous agent actions.
Qualifications
  • Systems thinker: Think in terms of platforms and long‑term leverage, not just features.
  • Production builder: Built and scaled ML infrastructure in production with meaningful business impact.
  • Ambiguity: Operate effectively in high ambiguity, turning unclear infra problems into clear direction.
  • Owner‑operator: Take ownership with a founder/owner‑operator mindset, act with urgency, and focus on outcomes.
  • Pace: Strong desire to move fast and deliver impact while maintaining sound engineering judgment.
  • Collaboration: Humble, collaborative, low‑ego, and elevate those around you.
  • Sustainability: Value work‑life balance as a foundation for sustained high performance.
  • Reliability mindset: Treat ML infra like any other production system – SLOs, on‑call, observability, postmortems.
Must Have
  • ML infra at scale: Built and operated production ML infrastructure on AWS – ECS, SageMaker, GPUs, autoscaling, and cost controls.
  • Inference platforms: Production experience with model serving for both LLMs and custom models; understands quantization, batching, and routing.
  • Provider breadth: Direct experience integrating with Google (Vertex/Gemini), OpenAI, and Anthropic APIs in production.
  • Training capability: Trained or fine‑tuned language models end‑to‑end; comfortable with deep learning, evaluation, and inference.
  • Cloud‑native engineering: Strong Python, Docker, dependency management, and CI/CD for AI workloads.
  • RAG & agents: Working knowledge of LangChain / LangGraph and modern RAG patterns over structured and unstructured data.
  • Cost optimization: Demonstrated experience reducing unit cost of AI workloads without regressing quality or latency.
  • AI safety & authorization: Hands‑on experience operating AI guardrails, scoped tool permissions, and authorization layers for production AI systems.
Nice to Have
  • Experience training small language models for production use.
  • GPU performance tuning (vLLM, TensorRT, Triton, or similar).
  • Prior staff‑level role at a company with a significant AI infra footprint.
  • Experience with ontology‑driven systems or knowledge graphs supporting AI applications.
  • Contributions to open‑source ML infrastructure or LLM tooling.
Compensation & Benefits
  • Base pay range: $200,000 – $250,000. Additional benefits and bonuses may apply.
  • Regular full‑time employees are eligible for benefits.
Statement of Equal Opportunity

At AppFolio, we value diversity in backgrounds and perspectives. We are a proud Equal Opportunity Employer and welcome applicants of all races, colors, religions, sexes, sexual orientations, gender identifications, national origins, ages, marital statuses, ancestries, physical or mental disabilities, or veteran status.

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