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Machine Learning Consultant Jobs in California (NOW HIRING)

Matroid

Deep Learning Field Engineer

Palo Alto, CA · On-site

... machine learning, or related fields. • Previous work experience in field engineering, professional services, consulting, or another customer-facing field. • Experience with high growth technology ...

Matroid

Deep Learning Field Engineer

Palo Alto, CA · On-site

... machine learning, or related fields. • Previous work experience in field engineering, professional services, consulting, or another customer-facing field. • Experience with high growth technology ...

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Machine Learning Consultant information

Is machine learning a high paying job?

Machine learning consultants typically earn high salaries due to the specialized skills required, such as programming, data analysis, and knowledge of algorithms. Salaries vary based on experience, location, and industry, but the role is generally considered well-compensated within the tech field.

What does a machine learning consultant do?

A Machine Learning Consultant helps businesses implement AI and machine learning solutions to improve decision-making, automate processes, and enhance efficiency. They analyze data, develop models, and provide strategic recommendations tailored to a company's needs. Their role often involves working with engineers, data scientists, and stakeholders to integrate machine learning into existing systems.

What are the key skills and qualifications needed to thrive as a machine learning consultant?

To thrive as a Machine Learning Consultant, you need strong expertise in machine learning algorithms, data analysis, and programming skills—typically supported by a degree in computer science, statistics, or a related field. Familiarity with tools such as Python, TensorFlow, PyTorch, and cloud platforms, as well as relevant certifications like AWS Certified Machine Learning or TensorFlow Developer, are highly beneficial. Excellent communication, problem-solving, and project management skills help consultants translate complex technical concepts for clients and efficiently drive projects. These skills and qualities are crucial for delivering effective machine learning solutions that address business needs and foster client trust.

How much does a machine learning consultant make?

The average salary for a machine learning consultant ranges from $80,000 to $150,000 annually, depending on experience, location, and industry. Senior consultants with specialized skills in programming languages like Python and tools such as TensorFlow can earn higher salaries, especially in competitive markets.

What does a typical project look like for a machine learning consultant?

As a Machine Learning Consultant, your projects often begin with collaborating closely with clients to understand their data challenges and business goals. You might be tasked with activities such as setting up data pipelines, selecting and training machine learning models, and presenting actionable insights. Projects can vary in length and scope, ranging from short-term advisory engagements to long-term implementations, and often involve teamwork with data engineers, business analysts, and IT departments. This dynamic environment means you need to balance hands-on technical work with client-facing responsibilities, ensuring successful delivery and measurable impact.

What are the most commonly searched types of Machine Learning Consultant jobs in California? The most popular types of Machine Learning Consultant jobs in California are:
What are popular job titles related to Machine Learning Consultant jobs in California? For Machine Learning Consultant jobs in California, the most frequently searched job titles are:
What job categories do people searching Machine Learning Consultant jobs in California look for? The top searched job categories for Machine Learning Consultant jobs in California are:
What cities in California are hiring for Machine Learning Consultant jobs? Cities in California with the most Machine Learning Consultant job openings:
Machine Learning Consultant jobs near you
Infographic showing various Machine Learning Consultant job openings in California as of August 2026, with employment types broken down into 1% As Needed, 64% Full Time, 30% Part Time, 3% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Machine Learning Engineer, LLM Fine-Tuning (San Jose)

First Soft Solutions LLC

San Jose, CA • On-site

Full-time

Re-posted 10 days ago

Job description

Machine Learning Engineer, LLM Fine‑Tuning

We are actively hiring for a Machine Learning Engineer focused on LLM fine‑tuning for Verilog/RTL applications.

Location: San Jose, CA (Onsite)

Skills: LLM fine‑tuning, Verilog/RTL, AWS, Bedrock, SageMaker

Responsibilities
  • Own the technical roadmap for Verilog/RTL‑focused LLM capabilities—from model selection and adaptation to evaluation, deployment, and continuous improvement.
  • Lead a hands‑on team of applied scientists/engineers: set direction, unblock technically, review designs/code, and raise the bar on experimentation velocity and reliability.
  • Fine‑tune and customize models using state‑of‑the‑art techniques (LoRA/QLoRA, PEFT, instruction tuning, preference optimization/RLAIF) with robust HDL‑specific evals:
    • Compile‑/lint‑/simulate‑based pass rates, pass@k for code generation, constrained decoding to enforce syntax, and “does‑it‑synthesize” checks.
  • Design privacy‑first ML pipelines on AWS:
    • Training/customization and hosting using Amazon Bedrock and SageMaker (or EKS + KServe/Triton/DJL) for bespoke training needs.
    • Artifacts in S3 with KMS CMKs; isolated VPC subnets & PrivateLink (including Bedrock VPC endpoints), IAM least‑privilege, CloudTrail auditing, and Secrets Manager for credentials.
    • Enforce encryption in transit/at rest, data minimization, no public egress for customer/RTL corpora.
  • Stand up dependable model serving: Bedrock model invocation where it fits, and/or low‑latency self‑hosted inference (vLLM/TensorRT‑LLM), autoscaling, and canary/blue‑green rollouts.
  • Build an evaluation culture: automatic regression suites that run HDL compilers/simulators, measure behavioral fidelity, and detect hallucinations/constraint violations; model cards and experiment tracking (MLflow/Weights & Biases).
  • Partner deeply with hardware design, CAD/EDA, Security, and Legal to source/prepare datasets (anonymization, redaction, licensing), define acceptance gates, and meet compliance requirements.
  • Drive productization: integrate LLMs with internal developer tools (IDEs/plug‑ins, code review bots, CI), retrieval (RAG) over internal HDL repos/specs, and safe tool‑use/function‑calling.
  • Mentor & uplevel: coach ICs on LLM best practices, reproducible training, critical paper reading, and building secure‑by‑default systems.
Qualifications
  • 10+ years total engineering experience with 5+ years in ML/AI or large‑scale distributed systems; 3+ years working directly with transformers/LLMs.
  • Proven track record shipping LLM‑powered features in production and leading ambiguous, cross‑functional initiatives at Staff level.
  • Deep hands‑on skill with PyTorch, Hugging Face Transformers/PEFT/TRL, distributed training (DeepSpeed/FSDP), quantization‑aware fine‑tuning (LoRA/QLoRA), and constrained/grammar‑guided decoding.
  • AWS expertise to design and defend secure enterprise deployments: Bedrock, SageMaker, S3, EC2/EKS/ECR, VPC/Subnets/Security Groups, IAM, KMS, PrivateLink, CloudWatch/CloudTrail, Step Functions, Batch, Secrets Manager.
  • Strong software engineering fundamentals: testing, CI/CD, observability, performance tuning; Python a must (bonus for Go/Java/C++).
  • Demonstrated ability to set technical vision and influence across teams; excellent written and verbal communication for execs and engineers.
Seniority Level

Mid‑Senior level

Employment Type

Full‑time

Job Function

Engineering and Information Technology

Industries

IT Services and IT Consulting

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About First Soft Solutions

Sourced by ZipRecruiter

First Soft Solutions custom application Development and Maintenance Services are designed to enable you to lower the total cost of ownership and the required quality for your application. While all application Development Outsourcing is Technically custom, The difference is that packaged applications were designed with a general set of features to be used by a broad range of users. Custom application development is capable of producing practically any feature you may desire for your site. Time and money are virtually the only limiting factors. Our goal is to provide Clients with the Solution that fits their specific and unique needs while giving them the knowledge they need to operate and maintain the New Systems and Software. Our allegiance is to the best solution for our Clients. Our experience and knowledgeable consultants are ready to go above and beyond expectations to assist you in obtaining your goals. We can also provides expert project management throughout the entire project life cycle.

Industry

It services

Company size

11 - 50 Employees

Headquarters location

East Brunswick, NJ, US

Year founded

2006

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