CrawlJobs Logo

Machine Learning Performance Modeling Architect

United States, Sunnyvale 178000.00 - 250000.00 USD / Year · Job Posted February 19, 2026
Apply Position
Job Link Share

Job Description

Reality Labs focuses on delivering Meta's vision through On-device AI. The compute performance and power efficiency requirements of these workloads require custom silicon. Reality Labs Silicon team is driving the state of the art forward with breakthrough work in computer vision, machine learning, mixed reality, displays, sensors, and new ways to map the human body. Our chips will enable On-device AI assistance and features, where our real and virtual world will mix and match throughout the day. We believe the only way to achieve our goals is to look at the entire stack, from transistors to architecture, firmware, and algorithms. We are seeking talented professionals to support the development and optimization of machine learning workloads and performance modeling for custom hardware and software platforms. In this role, you will contribute to analytical and simulation-based modeling and analysis, collaborating with cross-functional teams to build scalable and efficient solutions. Ideal candidates have a strong background in machine learning, system architecture, and performance modeling, and thrive in collaborative, hands-on environments.

Job Responsibility

  • Lead power/performance modeling and analysis of machine learning software-hardware components and use cases
  • Capture machine learning workloads from applications and system usages
  • Support all phases of Silicon SoC development
  • Contribute to execution of our silicon technology / machine learning roadmap to make beyond state-of-the-art advances in performance, power consumption and form factor
  • Work across disciplines, build new methodologies, juggle/coordinate multiple initiatives

Requirements

  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
  • 8+ years of experience in IP/SoC/System performance modeling and workload analysis/optimization for low-power/high-performance accelerators
  • 8+ years of experience with programming languages (C/C++ and Python), script automation and data visualization
  • Experience evaluating architectural tradeoffs in performance, power and image quality
  • Experience employing scientific methods to debug, diagnose and drive the resolution of complex, cross-disciplinary system issues

Nice to have

  • MS EE/CS or equivalent in relevant areas
  • Experience with building or modifying full-system performance simulators and analytical models
  • Experience with collecting and interpreting performance counters using SW profilers
  • Experience in machine workload development in Pytorch or similar ML toolchains
  • Experience with thermally constrained power/performance optimization in mobile devices
  • Experience operating under your own direction, driving high-level direction
  • Experience with telemetry generation and analysis
  • Experience with ML hardware architectures and use cases
  • Understanding of SoC and System architecture and heterogeneous compute principles
  • Experience Collaborating closely with the machine learning and system architecture teams to develop performance models for AR/VR machine learning software-hardware verticals
  • Experience supporting all phases of Silicon SoC development from a machine learning vertical modeling - from early definition on through specification, architecture and productization

What we offer

  • bonus
  • equity
  • benefits

Looking for more opportunities?

Search for other job offers that match your skills and interests.

Similar Jobs for

Machine Learning Performance Modeling Architect

8 matching positions

New

Machine Learning Software Engineer

In this role, you will design, build, and optimize robust ML models, data pipeli...
Location
Location
Canada , Calgary
Salary
Salary:
Not provided
https://www.randstad.com Logo
Randstad
Expiration Date
August 08, 2026
Flip Icon
Requirements
Requirements
  • BSc. or MSc. degree in Computer Science, Engineering, Mathematics, Physics, Statistics, or an equivalent quantitative discipline
  • Minimum of 3+ years of professional experience successfully delivering AI/ML projects
  • Minimum of 2+ years operating explicitly as a software developer within a structured delivery team
  • Mastery of ML algorithms, techniques, and Agentic frameworks, with the proven ability to optimize models with minimal supervision
  • Advanced expertise in at least two common development languages (e.g., Python, Java, C#)
  • Proficient working knowledge of general Python data packages and relational/non-relational databases and query engines (e.g., SQL)
  • Strong foundational knowledge of DevOps automation practices and building production solutions within AWS
  • Proficient with statistical concepts and capable of applying rigorous statistical thinking to solve complex business problems
Job Responsibility
Job Responsibility
  • Build, optimize, and scale machine learning models and end-to-end data pipelines
  • Design and implement critical operational aspects of model deployment, including automation pipelines, continuous monitoring, and automated drift detection
  • Transition experimental models and prototypes into robust, maintainable, and production-grade software applications
  • Participate in research experiments and rapid prototyping to validate next-generation AI concepts
  • Provide core software engineering expertise to internal data analytics and data science delivery teams
  • Apply strict software development best practices, including Test-Driven Development (TDD) and automated CI/CD workflows
  • Review requirements, map system dependencies, and provide accurate implementation effort estimations during team planning sessions
  • Test, debug, and optimize application code to eliminate performance bottlenecks
  • Conduct thorough code reviews and provide constructive feedback to elevate overall team code quality
  • Collaborate closely with architects, data scientists, product teams, and business stakeholders to translate high-level goals into functional ML architectures
What we offer
What we offer
  • Cutting-Edge AI Scope: Direct involvement in building and optimizing both traditional ML models and next-generation Agentic solutions with a high degree of autonomy
  • End-to-End Technical Ownership: Lead the operational deployment (MLOps) of AI models, directly influencing infrastructure automation, model tracking, and system performance
  • Cross-Functional Collaboration: Serve as the technical software anchor within a diverse ecosystem of data scientists, enterprise architects, and product managers
  • Modern Cloud Stack: Deepen your expertise in cloud-native deployment using AWS, enterprise data pipelines, and advanced platforms like Databricks
Read More
Arrow Right

Senior Machine Learning Engineer, Shopping AI

As the engine behind Zillow Group's mission to build a seamless digital real est...
Location
Location
United States
Salary
Salary:
163200.00 - 274300.00 USD / Year
Zillow
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • 3-5 years of experience in developing applications in search, personalized ranking, or recommender systems
  • Experience developing and deploying ML models that scale to high-traffic, latency sensitive customer-facing services (100s of millions of requests per day)
  • Strong programming skills in a high-level language such as Python or Java
  • Familiarity with common machine learning libraries like PyTorch, TensorFlow, Catboost, scikit-learn and huggingface (repository)
  • Expertise with large scale distributed data processing systems such as Hive, Spark, Airflow, or Databricks
  • Experience owning the full lifecycle of customer facing machine learning models, from offline experimentation and prototyping to online deployment, A/B testing, and performance monitoring
Job Responsibility
Job Responsibility
  • Design, build, and ship production new machine learning models that power core product features on the Zillow app, website, and email/push notifications
  • Re-architect our core home ranking and recommendation systems to support advanced neural networks and dramatically accelerate the pace of experimentation across surfaces
  • Own the full lifecycle of your models, from offline experimentation and prototyping with massive datasets to online deployment, A/B testing, and performance monitoring
  • Pioneer the application of cutting-edge deep learning and large language models (LLMs) to improve our home shopping experience
  • Develop new AI components that optimize how we display and when we recommend homes, ensuring we connect shoppers with the right content on the right properties at the right time
  • Collaborate in a cross-functional group of engineers, applied scientists, product managers, and designers to define, execute, and iterate on the team's strategic roadmap
  • Contribute to the team's engineering excellence by improving our machine learning infrastructure, development standards, and shared tooling
  • Act as a key technical voice, mentoring other engineers and helping to shape the long-term vision for artificial intelligence in the home shopping experience
What we offer
What we offer
  • Equity awards
  • Fulltime
Read More
Arrow Right

Principal Engineer (Machine Learning)

We are seeking a highly experienced Sr Principal ML Engineer with a good underst...
Location
Location
United States , Santa Clara
Salary
Salary:
185200.00 - 299475.00 USD / Year
paloaltonetworks.com Logo
Palo Alto Networks
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • 4+ years of experience using Python to build complex backend systems, ML experience is preferred. 10+ years of experience in software development
  • Strong background on machine learning and ML frameworks (e.g., TensorFlow, PyTorch)
  • Experience with cloud-native service development stack on GCP is a plus
  • Solid grasp of RESTful API design and micro services architecture
  • Skilled in diagnosing and solving complex problems while providing detailed technical analysis
  • Attention to details and high behavioral standards
  • Team player with can-do attitude to tackle difficult problems and you inspire your team to do the same
  • High energy and the ability to work in a fast-paced environment
  • Excellent collaboration and communication with multiple teams
  • Fast learner and eager to absorb new emerging technologies
Job Responsibility
Job Responsibility
  • Architect and implement new ML models and pipeline to support efficient model training, validation, and real-time inference
  • Optimize the existing ML models and pipeline
  • Ensure smooth integration of ML solutions into production systems, focusing on performance, reliability, and scalability
  • Build automation tools for continuous integration, delivery, and deployment of backend and ML components
  • Work closely with cross-functional teams (product, QA, DevOps, and customer support) to align development efforts with business needs
  • Troubleshoot and resolve complex issues that arise within both the backend infrastructure and ML models
  • Ensure code quality, security, and data privacy by following industry best practices
  • Maintain clear and concise documentation for system architecture, API endpoints, and ML model integration processes
What we offer
What we offer
  • restricted stock units
  • bonus
  • Fulltime
Read More
Arrow Right

Machine Learning Engineer, Zillow Shopping AI

As the engine behind Zillow Group's mission to build a seamless digital real est...
Location
Location
United States
Salary
Salary:
138300.00 - 232500.00 USD / Year
Zillow
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • 1-3 years of experience in developing applications in search, personalized ranking, or recommender systems
  • Experience developing and deploying ML models that scale to high-traffic, latency sensitive customer-facing services (100s of millions of requests per day)
  • Strong programming skills in a high-level language such as Python or Java
  • Familiarity with common machine learning libraries like PyTorch, TensorFlow, Catboost, scikit-learn and huggingface (repository)
  • Expertise with large scale distributed data processing systems such as Hive, Spark, Airflow, or Databricks
  • Experience owning the full lifecycle of customer facing machine learning models, from offline experimentation and prototyping to online deployment, A/B testing, and performance monitoring
Job Responsibility
Job Responsibility
  • Design, build, and ship production new machine learning models that power core product features on the Zillow app, website, and email/push notifications
  • Help re-architect our core home ranking and recommendation systems to support advanced neural networks and dramatically accelerate the pace of experimentation across surfaces
  • Own the full lifecycle of your models, from offline experimentation and prototyping with massive datasets to online deployment, A/B testing, and performance monitoring
  • Pioneer the application of cutting-edge deep learning and large language models (LLMs) to improve our home shopping experience
  • Develop new AI components that optimize how we display and when we recommend homes, ensuring we connect shoppers with the right content on the right properties at the right time
  • Collaborate in a cross-functional group of engineers, applied scientists, product managers, and designers to define, execute, and iterate on the team's strategic roadmap
  • Contribute to the team's engineering excellence by improving our machine learning infrastructure, development standards, and shared tooling
What we offer
What we offer
  • Eligible for equity awards based on factors such as experience, performance and location
  • Fulltime
Read More
Arrow Right

Sr Engineer, Machine Learning Engineering

The Senior Engineer, Machine Learning plays a pivotal role in advancing AI capab...
Location
Location
United States , Bellevue; Atlanta; Overland Park; Herndon
Salary
Salary:
127000.00 - 229100.00 USD / Year
https://www.t-mobile.com Logo
T-Mobile
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • Bachelor's Degree Computer Science, Data Science, Statistics, Informatics, Information Systems, Machine Learning, or another quantitative field
  • 1+ year of experience in designing, developing, and deploying large language models (LLMs) and generative AI systems in production environments
  • 5+ years of experience building and maintaining end-to-end ML pipelines, including data ingestion, training, deployment, monitoring, and optimization
  • 3+ years of experience applying MLOps practices and leveraging cloud platforms (AWS, GCP, or Azure) for scalable AI solutions
  • 5+ years of experience collaborating with cross-functional teams (engineering, data science, and product) to deliver AI-powered applications
  • 2+ years of experience in programming languages such as Python/R, Java/Scala, and/or Go, with hands-on experience in frameworks such as PyTorch, TensorFlow, LangChain, or Hugging Face
  • At least 18 years of age
  • Legally authorized to work in the United States
Job Responsibility
Job Responsibility
  • Build and manage the complete machine learning and generative AI lifecycle, including research, design, experimentation, development, deployment, monitoring, and maintenance
  • Design, develop, and deploy LLM-based and generative AI models to power scalable and intelligent enterprise applications
  • Architect, optimize, and maintain retrieval-augmented generation (RAG), prompt orchestration, and contextual reasoning pipelines to support diverse AI use cases
  • Implement scalable MLOps pipelines for model deployment, performance monitoring, and continuous improvement
  • Conduct fine-tuning, alignment, and evaluation of LLMs and multimodal models to ensure reliability, efficiency, and fairness
  • Collaborate with data science, engineering, and product teams to translate business needs into generative AI-driven solutions
  • Perform benchmarking, evaluation, and optimization of generative models to improve accuracy, latency, and cost efficiency
  • Research and apply emerging techniques in transformer architectures, multimodal learning, and generative modeling to drive innovation and enhance enterprise capabilities
  • Ensure secure, ethical, and responsible AI deployment, embedding fairness, transparency, and compliance throughout the model lifecycle
  • Mentor and guide team members on generative AI frameworks, best practices, and experimentation methodologies
What we offer
What we offer
  • annual stock grant
  • employee stock purchase plan
  • 401(k)
  • free, year-round money coaches
  • medical insurance
  • dental insurance
  • vision insurance
  • flexible spending account
  • paid time off
  • up to 12 paid holidays
  • Fulltime
Read More
Arrow Right

Senior Machine Learning Engineer

As Microsoft continues to push the boundaries of AI, we are on the lookout for p...
Location
Location
United States , Mountain View
Salary
Salary:
119800.00 - 258000.00 USD / Year
https://www.microsoft.com/ Logo
Microsoft Corporation
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research) OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.
Job Responsibility
Job Responsibility
  • Build and Deploy Models: Design, train, evaluate, and deploy machine learning models for natural language understanding tasks including intent detection, topic classification, conversation summarization, and user personas
  • Design ML Pipelines: Architect scalable, production-grade training and inference pipelines using Spark, Databricks, Azure ML and modern ML frameworks
  • NLP and Representation Learning: Develop and fine-tune transformer-based models and text encoders
  • build and maintain embedding pipelines and vector databases for semantic search and retrieval
  • Experimentation and Evaluation: Drive rigorous offline and online experimentation to measure model quality, iterate on architectures, and improve key product metrics
  • Collaborate Across Teams: Partner with data engineers, data scientists, and product teams to translate research insights into shipped features and align model outputs with product goals
  • Show Ownership Mindset: Proactively monitor model performance in production, diagnose regressions, and address scalability and reliability challenges before they become bottlenecks
  • Contribute Strategically: Identify opportunities to improve model architectures, training methodologies, and evaluation frameworks
  • mentor others on ML best practices
What we offer
What we offer
  • Certain roles may be eligible for benefits and other compensation
  • Fulltime
Read More
Arrow Right

Sr. Principal Machine Learning Engineer

Universal Ads is looking for a Sr. Principal Machine Learning Engineer to lead t...
Location
Location
United States
Salary
Salary:
192396.16 - 450928.49 USD / Year
comcastadvertising.com Logo
Comcast Advertising
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • Machine Learning (ML)
  • Collaborating
  • Advertising Technologies
  • 15 Years + work experience
Job Responsibility
Job Responsibility
  • Set vision and technical direction for the long-term ML strategy and roadmap for ad ranking at Universal Ads, including model architecture, infrastructure, and deployment frameworks
  • Architect and scale distributed ML systems capable of real-time decisioning across high-throughput ad environments
  • Partner with product and marketplace teams to align model performance with user and advertiser outcomes
  • Drive technical direction for cross-functional initiatives involving bidding algorithms, pacing, and system optimization
  • Shape technical culture, and ensure high standards for research rigor, reproducibility, and code quality
  • Establish strong experimentation and evaluation frameworks (A/B testing, counterfactual analysis, etc.) for model validation and pacing control
  • Represent Universal Ads externally in technical forums, publications, or conferences to shape the broader conversation around ML in advertising
  • Design and own ML data pipelines end-to-end, ensuring data cleanliness and freshness, and establishing the standards and infrastructure for reliable model inputs across ranking and pacing systems
What we offer
What we offer
  • Paid Time off
  • Physical Wellbeing
  • Financial Wellbeing
  • Emotional Wellbeing
  • Life Events + Family Support
  • Base pay
  • Bonus
  • Fulltime
Read More
Arrow Right

Machine Learning Tech Lead, GenAI

Provectus helps companies adopt ML/AI to transform the ways they operate, compet...
Location
Location
Salary
Salary:
Not provided
provectus.com Logo
Provectus
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • Proven experience with LLMs and NLP frameworks (e.g., Hugging Face, OpenAI, or Anthropic models)
  • Strong expertise in AWS Cloud Services
  • Strong experience in ML/AI, including at least 2 years in a leadership role
  • Hands-on experience with Python, TensorFlow/PyTorch, and model optimization
  • Familiarity with MLOps tools and best practices
  • Excellent problem-solving and decision-making abilities
  • Strong communication skills and the ability to lead cross-functional teams
  • Passion for mentoring and developing engineers
Job Responsibility
Job Responsibility
  • Lead and manage a team of 5-10 engineers, providing mentorship and fostering a collaborative team environment
  • Drive the roadmap for machine learning projects aligned with business goals
  • Coordinate cross-functional efforts with product, data, and engineering teams to ensure seamless delivery
  • Design, develop, and fine-tune LLMs and other machine learning models to solve business problems
  • Evaluate and implement state-of-the-art LLM techniques for NLP tasks such as text generation, summarization, and entity extraction
  • Stay ahead of advancements in LLMs and apply emerging technologies
  • Expertise in multiple main fields of ML: NLP, Computer Vision, RL, deep learning and classical ML
  • Architect and manage scalable ML solutions using AWS services (e.g., SageMaker, Lambda, Bedrock, S3, ECS, ECR, etc.)
  • Optimize models and data pipelines for performance, scalability, and cost-efficiency in AWS
  • Ensure best practices in security, monitoring, and compliance within the cloud infrastructure
What we offer
What we offer
  • Long-term B2B collaboration
  • Fully remote setup
  • Comprehensive private medical insurance or budget for your medical needs
  • Paid sick leave, vacation, public holidays
  • Continuous learning support, including unlimited AWS certification sponsorship
Read More
Arrow Right