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Machine Learning Architect Jobs (NOW HIRING)

Compunnel

Machine Learning Engineer

Plano, TX · On-site

Build and optimize ML-ready data pipelines and data architectures using Medallion Architecture ... Design and implement machine learning pipelines using Azure Databricks and related cloud ...

Virtu Financial

Machine Learning Researcher

New York, NY · On-site

$200K - $300K/yr

As a Machine Learning Researcher at Virtu, you'll pursue high-impact research opportunities within ... learning architecture design to training dynamics and execution strategy. Your innovations will ...

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Machine Learning Architect information

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$46.5K

$128.8K

$201.5K

How much do machine learning architect jobs pay per year?

As of Jun 19, 2026, the average yearly pay for machine learning architect in the United States is $128,756.00, according to ZipRecruiter salary data. Most workers in this role earn between $91,000.00 and $166,000.00 per year, depending on experience, location, and employer.

What typical projects or responsibilities might a Machine Learning Architect handle on a daily basis?

A Machine Learning Architect often leads the design and integration of scalable machine learning solutions, working closely with data scientists, engineers, and product managers to translate business problems into technical architectures. Daily tasks may include selecting appropriate ML models, overseeing data pipeline construction, defining system requirements, and ensuring best practices in model deployment and monitoring. They also review code, mentor junior team members, and collaborate across teams to align on project goals and timelines. The role offers a mix of hands-on technical work and strategic planning, providing a dynamic and impactful work environment.

What does a machine learning architect do?

A machine learning architect designs and develops machine learning systems and infrastructure to solve complex problems. They evaluate data, select appropriate algorithms, and oversee model deployment, often using tools like Python, TensorFlow, or cloud platforms. Strong programming skills and understanding of data architecture are essential for this role.

What is the salary of an ML architect?

The salary of a Machine Learning Architect typically ranges from $100,000 to $160,000 annually, depending on experience, location, and industry. Senior roles with advanced skills in deep learning, data engineering, and cloud platforms can earn higher compensation, often exceeding $180,000.

Which 5 jobs will survive AI?

Machine Learning Architects are likely to continue to be in demand as they design and oversee AI systems, requiring expertise in algorithms, data modeling, and programming. Roles that involve complex problem-solving, creativity, and human interaction—such as healthcare professionals, educators, skilled tradespeople, and creative designers—are also expected to persist despite AI advancements. These jobs typically require specialized skills, critical thinking, and emotional intelligence that AI cannot easily replicate.

What does a Machine Learning Architect do?

A Machine Learning Architect designs and oversees the implementation of machine learning systems, ensuring they are scalable, efficient, and aligned with business goals. They collaborate with data scientists, engineers, and stakeholders to define system architecture, select appropriate technologies, and optimize model deployment. Their role includes managing ML workflows, ensuring data pipeline integrity, and addressing challenges like model performance, scalability, and reliability.

What are the key skills and qualifications needed to thrive in the Machine Learning Architect position, and why are they important?

To thrive as a Machine Learning Architect, you need deep expertise in machine learning algorithms, data science, and software engineering, typically backed by an advanced degree in computer science or a related field. Familiarity with cloud platforms (like AWS, Azure, or GCP), ML frameworks (such as TensorFlow and PyTorch), and professional certifications in machine learning or data engineering is highly valuable. Exceptional problem-solving, leadership, and cross-functional communication skills help you effectively design solutions and collaborate with diverse technical teams. These skills are essential for architecting robust, scalable ML systems that align with business objectives and drive innovation.

Is ML a high paying job?

Machine Learning Architect roles are generally high-paying due to the specialized skills required, such as expertise in algorithms, programming, and data analysis. Salaries often vary based on experience, location, and industry, but they tend to be above average compared to many other tech positions.
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Machine Learning Architect jobs near you
Infographic showing various Machine Learning Architect job openings in the United States as of June 2026, with employment types broken down into 1% Locum Tenens, 4% As Needed, 83% Full Time, 11% Part Time, and 1% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $128,756 per year, or $61.9 per hour.

Machine Learning System Software Architect

Baidu USA

Sunnyvale, CA • On-site

Other

Posted 8 days ago

Job description

Do you want to be part of the AI revolution? Do you want to think out of the box, thriving on challenges in AI industry and the desire to solve them? Do you want to work with a world-class team to explore the fast-growing AI hardware opportunities and impact on AI industry?

We're looking forward to you joining us to collaborate, contribute, and revolutionize AI silicon and system.

Description

We are looking for a world-class Machine Learning System Software Architect to join our SoC team at Baidu's Sunnyvale office. The successful candidate will be a motivated self-starter who will thrive in this highly technical environment. Your job responsibilities as a Machine Learning System Software Architect will help the team to architect and create high-performance machine learning system software and build the distributed AI training system by connecting thousands of Kunlun Accelerators and servers.

Create differentiated architectural innovations for Baidu's Kunlun AI SoC roadmap. Architect, simulate, and design amazing machine learning solutions for our AI machine learning products.

Develop system-level ML architectures that push the boundaries of performance, power, and latency; and collaborate closely with many other teammates to ensure we design and optimize hardware and software for maximum performance.

Monitor industrial and academic trends in artificial intelligence and determine where they should intersect our roadmaps. Drive partnerships for access to the most advanced AI technologies

Evaluate the power, performance, and cost of prospective architecture and subsystems. Build scalable tools for modeling and performance evaluation.

Engage with system and application software engineers to ensure optimization of the entire hardware/software stack.

Work with SoC design, verification, and validation engineers to execute the architecture.

Qualifications

  • Knowledge of Machine Learning market, technological and business trends, software ecosystem, and emerging applications.
  • Proven track record of 5+ years architecting software solutions for Machine Learning, acceleration and optimization, especially in large distributed training system and HPC area.
  • Experience with deep learning frameworks: TensorFlow/PyTorch/PaddlePaddle, etc.
  • Strong track record of outreach to ML researchers and application developers.
  • Experience with CPUs, GPUs, memory systems, and accelerators.
  • Experience with performance simulation and modeling in C++
  • MS or PhD in Electrical or Computer Engineering.
  • Excellent communication skills in both English and Chinese.

Culture Fit:

  • Mission alignment: If you want to be part of a team to accomplish this great mission, we will provide you the best possible platform to do that.
  • Self-directed: We work best with people that are driven, motivated, and aspire to greatness.
  • Hungry to learn: We are eager to see you learn new skills and grow.
  • Team orientation: We work in small, fast-moving teams. We watch out for each other and go after big goals together as a team.

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