Staff Software Engineer AI/ML

$163K - $253K San Jose, CA, US Senior AI Software Engineer

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Skills & Technologies

AutogenCrewaiLangchainPythonPytorchTensorflow

About This Role

AI job market dashboard showing open roles by category

Please Note:

To provide the best candidate experience amidst our high application volumes, each candidate is limited to 10 applications across all open jobs within a 6\-month period.

Advancing the World's Technology Together

Our technology solutions power the tools you use every day\-including smartphones, electric vehicles, hyperscale data centers, IoT devices, and so much more. Here, you'll have an opportunity to be part of a global leader whose innovative designs are pushing the boundaries of what's possible and powering the future.

We believe innovation and growth are driven by an inclusive culture and a diverse workforce. We're dedicated to empowering people to be their true selves. Together, we're building a better tomorrow for our employees, customers, partners, and communities.

Advancing the World's Technology Together

Our technology solutions power the tools you use every day\-including smartphones, electric vehicles, hyperscale data centers, IoT devices, and so much more. Here, you'll have an opportunity to be part of a global leader whose innovative designs are pushing the boundaries of what's possible and powering the future.

We believe innovation and growth are driven by an inclusive culture and a diverse workforce. We're dedicated to empowering people to be their true selves. Together, we're building a better tomorrow for our employees, customers, partners, and communities.

About the Role

We are seeking a Senior Staff Engineer to build and optimize the EDA design environment and large\-scale compute infrastructure that supports our semiconductor design organizations, and to establish company\-wide standards and processes for EDA licensing and R\&D software. In this role, you will design and standardize the shared design environments and infrastructure used across multiple design organizations, driving engineering productivity and cost efficiency at scale.

AI/PI Group is an internal AI and Process Innovation organization within Samsung DSA, dedicated to transforming how our company works through artificial intelligence. We accelerate AI adoption across the entire organization — from reshaping day\-to\-day workflows and automating core internal processes to empowering our workforce with practical, intelligent tools. The Applied AI Engineering team is the driving force behind this vision, leading innovation at the intersection of machine learning and system engineering to develop and operate our next\-generation AI frameworks. We aim to enable frontier AI models to autonomously plan, retrieve information, coordinate with tools, and execute multi\-step workflows across our internal knowledge ecosystem. We are actively seeking talented Machine Learning Engineers specializing in building next\-generation AI/ML solutions.

What You'll Do

  • Design, build, and productize agentic AI applications that combine vision and language models — owning the architecture end\-to\-end from prototype through deployment and ongoing operation.
  • Architect multi\-agent systems using frameworks such as LangGraph, LangChain, AutoGen, or CrewAI, including agent orchestration, tool and function routing, state and memory management, error recovery, and human\-in\-the\-loop workflows.
  • Establish evaluation frameworks and quality bars for agentic and multimodal systems: define reference and non\-reference metrics, build benchmark suites and regression harnesses, and instrument agent trajectories for offline and online evaluation.
  • Drive quality, cost, and latency trade\-off decisions with data — selecting models, routing strategies, and inference configurations that meet product requirements within compute and memory budgets.
  • Optimize inference performance on accelerated hardware through quantization, batching, caching, kernel\- and runtime\-level tuning, and model/hardware co\-design; profile workloads to identify and eliminate bottlenecks.
  • Identify and solve multi\-discipline AI acceleration problems, especially with memory bottlenecks, involving algorithms, network design, hardware architecture
  • Work with researchers and application developers to enable the latest machine learning work to optimize performance.

What You Bring

  • BS with 10\+ years, MS with 8\+ years, or PhD with 5\+ years of experience in Computer Science, Electrical Engineering, or a related field
  • Demonstrated track record of deploying and operating LLM\- or vision\-powered systems in production, with proven experience in evaluation and safe rollout practices (A/B testing, canary releases, offline/online evaluation) — including defining quality metrics, benchmarking models, and driving quality/cost/latency trade\-off decisions
  • Hands\-on expertise with agentic AI frameworks (LangGraph, CrewAI, ADK) — multi\-agent orchestration and patterns, tool routing, state management, and/or interoperability protocols (MCP, A2A)
  • Experience with LLM inference optimization and serving (e.g., vLLM, TensorRT\-LLM), covering quantization, KV\-cache management, and hardware\-aware deployment
  • Strong Python and C/C\+\+ skills with deep experience in PyTorch/TensorFlow, and experience designing, building, and securing large\-scale distributed systems

Preferred Qualification

  • PhD of software engineering experience
  • MLOps exposure: prompt/version management, monitoring, observability
  • Experience with ML, graphics or computer vision accelerator
  • Understanding of PPA (performance, power, and area) trade\-offs, memory controller architecture and/or general computer architecture is beneficial
  • Familiarity with state\-of\-the\-art AI workloads and their compute and memory requirements
  • Experience with performance modeling of heterogenous systems is beneficial
  • Ability to meet aggressive project deadlines in a team environment

\#LI\-VL1

Equal Opportunity Employment Policy

Samsung Semiconductor takes pride in being an equal opportunity workplace dedicated to fostering an environment where all individuals feel valued and empowered to excel, regardless of race, religion, color, age, disability, sex, gender identity, sexual orientation, ancestry, genetic information, marital status, national origin, political affiliation, or veteran status.

When selecting team members, we prioritize talent and qualities such as humility, kindness, and dedication. We extend comprehensive accommodations throughout our recruiting processes for candidates with disabilities, long\-term conditions, neurodivergent individuals, or those requiring pregnancy\-related support. All candidates scheduled for an interview will receive guidance on requesting accommodations.

Our Commitment to Innovation and Fairness

At Samsung Semiconductor, we use Artificial Intelligence (AI) tools in the recruitment process to enhance efficiency. However, AI is used as a support tool, not a final decision\-maker. All hiring decisions are made by our human recruiting team and hiring managers to ensure every candidate is evaluated fairly and holistically.

Recruiting Agency Policy

We do not accept unsolicited resumes. Only authorized recruitment agencies that have a current and valid agreement with Samsung Semiconductor, Inc. are permitted to submit resumes for any job openings.

Applicant AI Use Policy

At Samsung Semiconductor, we support innovation and technology. However, to ensure a fair and authentic assessment, we ask that candidates rely on their own knowledge and skills throughout the process. AI tools may be used for basic preparation, grammar, and research, but should not be used to generate or assist with submitted content or live interview responses. If we determine that AI is being used outside these guidelines, we reserve the right to pause or end the interview, and your candidacy may be disqualified.

Trade Secret Notice

By submitting an application, you agree not to disclose to Samsung—or encourage Samsung to use—any confidential or proprietary information (including trade secrets) belonging to a current or former employer or other entity.

Applicant Privacy Policy

https://semiconductor.samsung.com/about\-us/careers/us/privacy/

Salary Context

This $163K-$253K range is above the median for AI Software Engineer roles in our dataset (median: $185K across 231 roles with salary data).

Role Details

Title Staff Software Engineer AI/ML
Location San Jose, CA, US
Category AI Software Engineer
Experience Senior
Salary $163K - $253K
Remote No

About This Role

AI Software Engineers build the applications and systems that AI models run inside. They own the API layers, data pipelines, frontend integrations, and infrastructure that turn a model into a product users interact with. Every AI company needs engineers who can build the software around the AI.

The challenge is building reliable systems around inherently unreliable components. Models are probabilistic. They'll give different answers to the same question. They hallucinate. They're slow. They're expensive. Your job is to build an application layer that handles all of this gracefully while delivering a product that users trust and enjoy.

Across the 4,317 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At Samsung Semiconductor Inc (US), this role fits into their broader AI and engineering organization.

AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.

What the Work Looks Like

A typical week includes: building API endpoints that serve model inference with caching and fallback logic, designing the data pipeline that feeds context to a RAG system, implementing streaming responses in the frontend, debugging a race condition in the async inference pipeline, and optimizing database queries for the vector search layer. It's full-stack engineering with AI at the center.

AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.

Skills Required

Autogen (3% of roles) Crewai (3% of roles) Langchain (9% of roles) Python (52% of roles) Pytorch (15% of roles) Tensorflow (12% of roles)

Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.

Knowledge of vector databases, embedding APIs, and LLM integration patterns (function calling, structured outputs, retry logic) differentiates AI software engineers from general software engineers. Understanding cost optimization (caching strategies, model routing, batched inference) is valuable since inference costs can dominate application economics.

Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.

Compensation Benchmarks

AI Software Engineer roles pay a median of $218,500 based on 729 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($208K) sits 5% below the category median. Disclosed range: $163K to $253K.

Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.

Samsung Semiconductor Inc (US) AI Hiring

Samsung Semiconductor Inc (US) has 1 open AI role right now. They're hiring across AI Software Engineer. Based in San Jose, CA, US. Compensation range: $253K - $253K.

Location Context

Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 median).

Career Path

Common paths into AI Software Engineer roles include Software Engineer, Full-Stack Developer, Backend Engineer.

From here, career progression typically leads toward Staff Engineer, AI Architect, Engineering Manager.

If you're a software engineer, you're already 80% there. Learn the AI integration patterns: RAG, streaming inference, function calling, structured outputs. Build a project that demonstrates you can wrap an AI model in a production-quality application with proper error handling, caching, and user experience. That's the portfolio piece that gets you hired.

What to Expect in Interviews

Technical screens look like standard software engineering interviews with an AI twist. Expect system design questions about building reliable applications around probabilistic models: handling streaming responses, implementing retry logic for API failures, and designing caching strategies for LLM outputs. Coding rounds test standard algorithms plus practical integration patterns like async processing and rate limiting.

When evaluating opportunities: Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.

AI Hiring Overview

The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.

The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).

AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.

The AI Job Market Today

The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.

The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (138) are outnumbered by mid-level (2,071) and senior (1,655) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 453 positions, representing the bottleneck between technical execution and organizational strategy.

Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.

AI compensation is structured in clear tiers. The market median sits at $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.

Category matters for compensation. AI Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.

The most in-demand skills across all AI postings: Python (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.

Frequently Asked Questions

Based on 729 roles with disclosed compensation, the median salary for AI Software Engineer positions is $218,500. Actual compensation varies by seniority, location, and company stage.
Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.
About 15% of the 4,317 AI roles we track offer remote work. Remote availability varies by company and seniority level, with senior and leadership roles more likely to offer location flexibility.
Samsung Semiconductor Inc (US) is among the companies actively hiring for AI and ML talent. Check our company profiles for detailed breakdowns of open roles, salary ranges, and hiring trends.
Common next steps from AI Software Engineer positions include Staff Engineer, AI Architect, Engineering Manager. Progression depends on whether you lean toward technical depth, people management, or product strategy.

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