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Linear Programming Jobs in California (NOW HIRING)

Nace AI

Machine Learning Engineer

Palo Alto, CA · On-site

Deep knowledge in Linear Programming . * Experience with advanced NLP and Multimodal post-training experience (e.g., model distillation, quantization, deployment optimization). * Experienced in ...

Adidev Technologies Inc

Data Science

San Francisco, CA · On-site

Optimization (Linear programming, Stochastic Gradient Descent, Genetic Algorithm etc.) * Experience with neural network approaches to text classification CNN, RNN, LSTM,Keras * Machine Learning ...

Intel

Operations Research Engineer

Folsom, CA · On-site

$149K - $211K/yr

Foundation in Operations Research (OR) methodologies, Linear Programming, Integer Programming, and Constraint Programming techniques. Preferred Qualifications: 2+ years of hands-on experience in ...

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Linear Programming information

See California salary details

$43.9K

$69.9K

$97.7K

How much do linear programming jobs pay per year?

As of Jun 13, 2026, the average yearly pay for linear programming in California is $69,929.00, according to ZipRecruiter salary data. Most workers in this role earn between $50,300.00 and $87,300.00 per year, depending on experience, location, and employer.

What jobs pay $10,000 a month without a degree?

Jobs related to linear programming, such as data analysts, operations managers, or supply chain consultants, can pay $10,000 or more monthly without a formal degree if they have strong analytical skills, experience, and proficiency with optimization tools. Many of these roles focus on problem-solving, software tools like Excel or specialized optimization software, and industry experience rather than formal education credentials.

What careers use linear programming?

Linear programming is used in careers such as operations research analysts, supply chain managers, financial analysts, and industrial engineers. These roles involve optimizing processes, resource allocation, and decision-making using mathematical models and tools like Excel Solver or specialized software. Strong analytical skills and knowledge of optimization techniques are essential in these fields.

What jobs pay 2000 a day?

High-paying jobs related to linear programming often include roles such as quantitative analysts, management consultants, or senior data scientists, especially in finance, consulting, or technology sectors. These positions typically require advanced skills in optimization, programming, and data analysis, and may involve long hours or project-based work to reach such daily earnings.

What is a Linear Programming job?

A Linear Programming job involves using mathematical optimization techniques to maximize or minimize a particular objective, such as cost reduction or resource allocation, under a set of given constraints. Professionals in this field work with mathematical models, algorithms, and software tools like Python, MATLAB, or specialized solvers. These jobs are common in industries like logistics, finance, operations research, and data science, where efficient decision-making is critical.

What are the key skills and qualifications needed to thrive in the Linear Programming position, and why are they important?

To succeed in a Linear Programming role, you need strong mathematical and analytical skills, typically supported by a degree in operations research, mathematics, or a related quantitative field. Familiarity with optimization software such as CPLEX, Gurobi, or MATLAB, along with programming knowledge in Python or R, is often required. Excellent problem-solving abilities, attention to detail, and clear communication are valuable soft skills in this position. These skills and qualities are crucial for effectively modeling, analyzing, and solving complex optimization problems that drive organizational decision-making.

What jobs pay $500,000 a year in the US?

In the field of linear programming and related quantitative roles, high-paying jobs such as quantitative analysts, data scientists, and operations research managers can reach or exceed $500,000 annually, especially with experience, advanced skills in optimization, and working in finance, consulting, or technology sectors. These roles often require strong analytical skills, programming knowledge, and advanced degrees like a master's or Ph.D. in a related field.

What are the typical responsibilities of someone working in a Linear Programming role?

Professionals specializing in Linear Programming are responsible for developing mathematical models to optimize processes such as resource allocation, scheduling, or logistics. Their daily tasks often include collecting and analyzing data, formulating objective functions and constraints, coding and testing optimization algorithms, and interpreting solutions for practical implementation. Collaboration with cross-functional teams such as data analysts, engineers, and business stakeholders is common to ensure models accurately address real-world challenges. By transforming large and complex datasets into actionable insights, these professionals play a key role in improving efficiency and supporting data-driven decisions across industries.

What are the most commonly searched types of Linear Programming jobs in California? The most popular types of Linear Programming jobs in California are:
What are popular job titles related to Linear Programming jobs in California? For Linear Programming jobs in California, the most frequently searched job titles are:
What job categories do people searching Linear Programming jobs in California look for? The top searched job categories for Linear Programming jobs in California are:
What cities in California are hiring for Linear Programming jobs? Cities in California with the most Linear Programming job openings:
Linear Programming jobs near you
Infographic showing various Linear Programming job openings in California as of June 2026, with employment types broken down into 4% As Needed, 49% Full Time, 17% Part Time, 4% Temporary, 22% Contract, and 4% Nights. Highlights an 65% Physical, 5% Hybrid, and 30% Remote job distribution, with an average salary of $69,929 per year, or $33.6 per hour.

Machine Learning Engineer

Nace AI

Palo Alto, CA • On-site

Full-time

Posted 25 days ago

Job description

Role Overview:
As a Machine Learning Engineer, you will play a central role in translating cutting-edge machine learning research into scalable, production-ready solutions. You will collaborate closely with cross-functional teams to identify opportunities where ML can drive product value, architect robust model-centric systems, and ensure their seamless integration into real-world applications. The role requires a strong balance between theoretical understanding and engineering execution, with a focus on building reliable, maintainable, and high-impact AI-driven features that align with Nace.AI's strategic objectives.
Key Responsibilities:
  • Design, build, and maintain end-to-end ML systems, including synthetic data pipelines, model training, debugging, and performance evaluation.
  • Fine-tune large language models (LLMs) and implement meta-learning methods to enhance model generalization and efficiency.
  • Improve existing Nace.AI models by incorporating advancements from recent ML research.

Qualifications:
  • Hands-on experience training and fine-tuning large language models (LLMs) and vision-language models (VLMs), including practical work with pre-training, instruction tuning, and alignment techniques (GRPO,RLHF/DPO/PPO).
  • Hands-on Experience with Deep Learning Models, especially Transformers.
  • Ability to translate cutting-edge research from papers into clean, production-ready code (Paper to Code).
  • Proven experience scaling inference infrastructure for LLMs/VLMs, including expertise in model serving frameworks like vLLM, TGI.
  • Proficient in Python with a strong track record of building substantial projects.
  • Solid foundation in computer science fundamentals (data structures, algorithms, design patterns).
  • BS degree in CS or related technical field.
  • Solid Experience with ML frameworks and libraries (PyTorch, TensorFlow).
  • Self-starter comfortable working in a fast-paced, dynamic environment.

Preferred Qualifications:
  • MS/PhD in CS or related technical field.
  • Familiarity with data processing stacks such as Spark and Airflow.
  • Experience with multi-node GPU training.
  • Contributor to open-source ML projects.
  • Deep knowledge in Linear Programming.
  • Experience with advanced NLP and Multimodal post-training experience (e.g., model distillation, quantization, deployment optimization).
  • Experienced in inference time optimization, deep understanding of LLM serving optimizations for LLMs/VLMs.
  • Hands on experience with quantization techniques (AWQ, GPTQ, FP8/GGUF).

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