Machine Learning Engineer job in San Jose, CA

Are you a forward-thinking technologist with a passion for building intelligent systems that drive real-world impact? We are seeking a Machine Learning Engineer to join a fast-growing AI-focused company in San Jose, CA. This is an exceptional opportunity to contribute to cutting-edge machine learning models, solve complex data problems, and innovate at the intersection of technology and business. If you thrive in a collaborative, research-driven environment and have a knack for deploying scalable ML solutions, this role is built for you.

Engineer the Future of AI in San Jose

A leading technology company based in San Jose, CA is on the lookout for a talented Machine Learning Engineer to help power its next generation of AI products. The ideal candidate brings a strong background in machine learning algorithms, deep learning frameworks, and data science practices. If you’re ready to push the boundaries of artificial intelligence and contribute to breakthrough innovations in a high-impact environment, this is your moment to lead and grow.

Key Responsibilities of the Machine Learning Engineer – San Jose, CA

Model Development & Optimization: Design, develop, and refine machine learning models that solve complex business problems. Leverage supervised, unsupervised, and reinforcement learning techniques to improve prediction accuracy, performance, and scalability.

Data Analysis & Feature Engineering: Analyze large, complex datasets to extract actionable insights. Build robust data pipelines and engineer meaningful features to enhance model performance and adaptability.

Algorithm Research & Innovation: Stay current with the latest research in machine learning, deep learning, and AI. Apply novel algorithms and techniques to push the boundaries of existing solutions and contribute to the company’s intellectual property.

End-to-End Deployment: Collaborate with engineering and product teams to deploy models into production environments. Ensure models are scalable, maintainable, and integrated seamlessly into real-time applications or APIs.

Performance Monitoring & Improvement: Continuously monitor model performance post-deployment. Implement retraining strategies, diagnose drift issues, and adjust models based on feedback and evolving datasets.

Cross-Functional Collaboration: Work closely with data scientists, product managers, software engineers, and stakeholders to align ML initiatives with business goals. Translate complex technical findings into clear, actionable insights.

Experimentation & A/B Testing: Design and run experiments to validate model improvements and feature enhancements. Analyze experiment results and iterate quickly to achieve optimal outcomes.

Code Quality & Documentation: Write clean, efficient, and well-documented code. Contribute to code reviews, establish best practices for ML model development, and maintain model version control.

Tooling & Infrastructure: Utilize and improve internal tools for ML experimentation, training, and deployment. Work with cloud platforms (AWS, GCP, Azure) and ML Ops tools to streamline development workflows.

Ethics & Responsible AI: Ensure models are fair, explainable, and unbiased. Adhere to ethical AI practices, considering potential impacts and implementing safeguards to prevent misuse or harm.

What the Client is Looking for in You

As a Machine Learning Engineer, the client is seeking a highly skilled and innovative professional with a passion for building intelligent systems that solve complex real-world problems. You should be a results-driven individual who thrives in a fast-paced, data-rich environment and is capable of developing models that deliver measurable impact to the business.

Proven Experience in Machine Learning and AI

The ideal candidate brings hands-on experience in designing, building, and deploying machine learning models across varied use cases. You should have a strong command of ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn), a deep understanding of algorithms, and practical experience with large-scale data processing. Demonstrated success in driving model accuracy, improving performance metrics, or building customer-centric AI features is highly valued.

Strong Problem-Solving and Analytical Thinking

You must be a critical thinker with the ability to break down complex business problems into data-driven solutions. The client values engineers who can explore raw data, uncover hidden patterns, and implement predictive or classification models that support smarter decisions and user experiences.

Production-Ready Engineering Skills

Beyond research, the client is looking for a builder—someone who can write clean, efficient code and deploy models to production at scale. Familiarity with APIs, containerization (Docker/Kubernetes), cloud platforms (AWS, GCP, Azure), and ML Ops practices will set you apart. The ability to work across the full ML lifecycle—from data ingestion to deployment and monitoring—is key.

Collaborative and Cross-Functional Mindset

Success in this role requires working closely with data scientists, product managers, software engineers, and business leaders. The client is looking for a team player who can communicate technical concepts clearly and translate ML insights into business value. Your ability to adapt and collaborate in an agile environment is essential.

Intellectual Curiosity and Continuous Learning

The client values individuals who are constantly learning and staying up to date with the latest research and industry developments. A passion for innovation and applying new techniques in deep learning, NLP, computer vision, or recommendation systems will be highly appreciated.

Strong Communication and Documentation Skills

You should be able to communicate technical findings effectively, both verbally and in writing. The client expects well-documented code, clear experiment logs, and concise presentations that support decision-making across teams and stakeholders.

Ethical AI and Responsible Development

A commitment to ethical AI practices is important. The client is looking for someone who can build fair, interpretable, and bias-aware models, and who actively considers the broader impact of machine learning on users and society.

FAQs About the Role – Machine Learning Engineer – San Jose, CA

1. What are the key responsibilities of a Machine Learning Engineer in this role?
As a Machine Learning Engineer, you will be responsible for developing and deploying machine learning models to solve real-world business problems. This includes designing algorithms, engineering features, building data pipelines, and integrating models into production systems. You will collaborate with cross-functional teams to ensure model performance, scalability, and accuracy, while continuously monitoring and refining solutions based on real-time data.

2. What qualifications and experience are required for this position?
The ideal candidate should have a strong background in machine learning, data science, and software engineering. Proficiency in Python, machine learning frameworks (such as TensorFlow, PyTorch, or Scikit-learn), and experience with cloud platforms (AWS, GCP, or Azure) are essential. A bachelor’s or master’s degree in Computer Science, Data Science, or a related field is required; a Ph.D. or equivalent research experience is a plus. Prior experience deploying ML models in production environments is highly desirable.

3. What technical skills are essential for success in this role?
You should have expertise in supervised and unsupervised learning, deep learning, data preprocessing, and model evaluation techniques. Familiarity with data engineering tools, version control (Git), containerization (Docker/Kubernetes), and ML Ops practices will be highly valued. Strong problem-solving skills, attention to detail, and the ability to write clean, well-documented code are also crucial.

4. What are the biggest challenges I may face in this role?
You may encounter challenges such as working with noisy or imbalanced datasets, ensuring model interpretability, and addressing performance trade-offs in real-time systems. Balancing model accuracy with latency, scalability, and fairness can also be complex. Staying up to date with rapidly evolving ML technologies and aligning model outcomes with business goals will be key ongoing challenges.

5. How does this role impact the company’s mission and success?
Your work as a Machine Learning Engineer will directly contribute to the company’s innovation strategy and decision-making processes. The models you build will enable data-driven features, optimize user experiences, automate operations, and uncover new business opportunities. You will play a critical role in helping the organization scale its AI initiatives and gain a competitive edge in the market.

6. What is the company’s culture and work environment like?
The company promotes a collaborative, intellectually curious, and agile work environment. You’ll be part of a multidisciplinary team that values continuous learning, experimentation, and innovation. Employees are encouraged to take ownership of projects, contribute ideas, and stay at the forefront of emerging technologies. A supportive atmosphere with a focus on work-life balance and professional development is core to the company’s culture.

What Remuneration Can You Expect from This Job?

As a Machine Learning Engineer based in San Jose, CA, you can expect a competitive compensation package that reflects both the high demand for AI expertise and the cost of living in Silicon Valley. The package typically includes:

1. Base Salary

The annual base salary for a Machine Learning Engineer in San Jose typically ranges from $120,000 to $180,000, depending on your experience, education, and technical skill set. Senior engineers or those with advanced degrees and specialized domain knowledge (e.g., NLP, computer vision, or recommendation systems) may command salaries on the higher end or above this range.

2. Performance-Based Bonuses

Many employers offer performance-based bonuses tied to individual, team, or company performance. These can range from 10% to 25% of the base salary annually, based on contributions to project success, product impact, or business growth.

3. Equity & Stock Options

As a tech hub, San Jose companies—especially startups and mid-to-large tech firms—often include equity compensation in the form of stock options or restricted stock units (RSUs). These align your success with the company’s long-term growth and can offer significant financial upside.

4. Signing Bonuses & Relocation Support

Top candidates, particularly those with in-demand skills or coming from prestigious programs or employers, may be offered signing bonuses ranging from $5,000 to $25,000. For non-local hires, companies may also provide relocation assistance, especially in competitive hiring environments.

5. Benefits & Perks

Machine Learning Engineers typically receive a comprehensive suite of benefits, including:

Health, dental, and vision insurance
401(k) plans with employer matching
Paid time off (PTO), holidays, and parental leave
Wellness stipends or gym memberships
Educational or conference reimbursement
Remote work options or hybrid flexibility
Onsite meals, commuter assistance, or tech equipment stipends

6. Career Growth & Learning Opportunities

While not always quantified financially, many companies invest heavily in career development, including access to advanced learning platforms, research opportunities, mentorship, and internal mobility programs that can lead to rapid career advancement and increased earning potential.

Total Compensation Potential

Including base salary, bonuses, and equity, a Machine Learning Engineer in San Jose can expect a total annual compensation package ranging from $140,000 to $250,000+, with senior or lead roles exceeding this range at top-tier firms or unicorn startups.

How to Apply

If you are a highly motivated Machine Learning Engineer with a passion for solving complex problems through data and AI, we invite you to apply for this exciting opportunity in San Jose, CA. This role offers the chance to work on cutting-edge technologies, collaborate with top-tier engineering teams, and contribute to real-world innovation in a dynamic tech environment.

To apply, please submit your updated resume along with a cover letter highlighting your experience in building and deploying machine learning models, working with large-scale datasets, optimizing algorithms, and collaborating with cross-functional teams. Be sure to detail your proficiency in Python, ML frameworks, data engineering tools, and your ability to translate business needs into scalable machine learning solutions.

This position provides a rewarding career path for engineers eager to push the boundaries of AI, contribute to impactful products, and grow within a high-performance organization. Apply now to take the next step in your career as a Machine Learning Engineer in San Jose, CA!

For more information or to explore similar AI and Data Science roles, visit our Machine Learning Engineer Recruiters Page.

Job Category: Machine Learning Engineer

Job Type: Full Time

Job Location: San Jose

Machine Learning Engineer job in San Jose, CA