Machine Learning Architect Job Description Template

Sopiko Mamulashvili

Last updated on February 14, 2025 | 8 min read

Job Description Template

General overview of the role

A Machine Learning Architect is responsible for designing, developing, and deploying machine learning systems, models, and algorithms tailored to meet the needs of an organization. This role requires a deep understanding of machine learning theory and hands-on expertise in building scalable, efficient, and robust ML solutions that address complex business challenges. Machine Learning Architects work at the intersection of data science, engineering, and AI research, ensuring that ML models are optimized for production environments and aligned with business objectives. They also define best practices, oversee the ML pipeline, and collaborate with cross-functional teams to integrate AI-driven insights into enterprise applications.

Typical duties and responsibilities

• Design and implement machine learning models and architectures, ensuring scalability, robustness, and efficiency in production environments.
• Lead the end-to-end development of machine learning solutions, including data preprocessing, feature engineering, model selection, training, and evaluation.
• Collaborate with data scientists, engineers, and business stakeholders to define ML requirements and deploy AI-driven solutions that align with business objectives.
• Oversee the machine learning pipeline, from data collection and processing to model deployment, monitoring, and optimization.
• Develop algorithms and techniques to enhance the accuracy, reliability, and performance of models in real-world applications.
• Evaluate and implement new machine learning frameworks, technologies, and research advancements to drive continuous innovation.
• Ensure seamless integration of machine learning models with existing enterprise systems, cloud platforms, and big data pipelines.
• Provide technical leadership and mentorship to junior data scientists, ML engineers, and software developers.
• Establish and promote best practices for MLOps, model versioning, monitoring, and automated retraining.
• Work closely with security and compliance teams to ensure data privacy, regulatory compliance, and ethical AI principles in ML applications.

Required skills and experience

• Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field (Master’s or PhD preferred).
• 5+ years of experience in designing and deploying machine learning models and AI-driven applications.
• Expertise in programming languages such as Python, Java, or Scala, with hands-on experience in ML frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn, Keras).
• Deep understanding of machine learning algorithms, statistical modeling, and AI techniques, including deep learning, reinforcement learning, and NLP.
• 3+ years of experience working with cloud platforms (AWS, Azure, Google Cloud) and deploying ML models in cloud-native environments.
• Strong knowledge of data structures, algorithms, and distributed computing for handling large-scale datasets.
• Experience in MLOps, CI/CD for ML models, and model monitoring tools.
• Familiarity with big data platforms (e.g., Apache Spark, Hadoop, Databricks) and experience managing large-scale machine learning workflows.
• Strong problem-solving skills, analytical thinking, and the ability to communicate complex AI concepts to non-technical stakeholders.

Nice to have/preferred skills and experience

• Experience with model interpretability tools and techniques to ensure transparency and fairness in AI models.
• Familiarity with containerization and orchestration tools like Docker and Kubernetes for deploying ML models at scale.
• Contributions to open-source machine learning projects or AI research publications.
• Knowledge of MLOps best practices, including automated model retraining, versioning, and performance tracking.
• Experience deploying AI solutions in production environments with a focus on reliability, scalability, and optimization.

Machine Learning Architect salary

Salaries for Machine Learning Architects vary based on experience, industry, and location:

• Entry-level Machine Learning Architects typically earn between $120000 – $140000 annually.
• Mid-level professionals can earn between $140000 – $170000 annually.
• Senior Machine Learning Architects and those working in enterprise AI projects may earn $180000 or more
  annually.

How can I become a good Machine Learning Architect?

• Gain strong expertise in machine learning algorithms, statistical modeling, and AI technologies.
• Develop hands-on experience with ML frameworks like TensorFlow, PyTorch, and Scikit-learn.
• Master cloud-based machine learning (AWS SageMaker, Azure ML, Google Vertex AI) and big data platforms for handling large-scale ML workloads.
• Stay updated with cutting-edge AI research, reinforcement learning, and ethical AI principles.
• Learn MLOps best practices, including model deployment, version control, and performance monitoring.
• Work on real-world ML projects and contribute to open-source AI initiatives.
• Build strong problem-solving and analytical skills to develop efficient ML architectures for business use cases.
• Develop excellent communication skills to effectively collaborate with engineers, data scientists, and business leaders.

What are the key Machine Learning Architect skills?

Hard skills

• Expertise in ML algorithms, deep learning, and AI frameworks (TensorFlow, PyTorch, Keras, Scikit-learn).
• Proficiency in programming languages (Python, Java, Scala) for AI development.
• Experience with cloud ML platforms (AWS SageMaker, Azure ML, Google Vertex AI).
• Strong understanding of distributed computing and big data platforms (Apache Spark, Hadoop).
• Knowledge of MLOps tools for automating model deployment and monitoring.
• Experience with containerization and orchestration tools (Docker, Kubernetes).

Soft skills

• Strong analytical and problem-solving skills to optimize AI models for real-world applications.
• Excellent collaboration and communication skills to work with engineers, stakeholders, and business leaders.
• Ability to translate complex AI concepts into actionable business insights.
• Strong attention to detail and adaptability in an evolving AI landscape.

Why join us as a Machine Learning Architect?

• Work with cutting-edge AI and machine learning technologies in a fast-paced, innovative environment.
• Collaborate with highly skilled data scientists, engineers, and business leaders to build impactful AI solutions.
• Enjoy opportunities for career growth, leadership development, and continuous learning.
• Be part of a company that prioritizes AI-driven innovation and fosters a culture of technological excellence.
• Access competitive salaries, comprehensive benefits, and a strong work-life balance.

What we offer

• Extensive health and wellness coverage.
• Work-from-home options and flexible hours.
• Paid time off for vacations, holidays, and sick leave.

Here are a few more benefits that, according to Forbes, are valued by employees:

• Retirement savings plans with employer matching, such as 401(k) plans, are significant to employees.
• Early leave on Fridays.
• 4-day work week.
• Private dental insurance.

About us

We recommend including general information about the company, such as its mission, values, and industry focus. For instance, you could say:

“DevsData LLC is an IT recruitment agency that connects top tech talent with leading companies to drive innovation and success. Their diverse team of US specialists brings unique viewpoints and cultural insights, boosting their capacity to meet client demands and build inclusive work cultures. Over the past 8 years, DevsData LLC has successfully completed more than 80 projects for startups and corporate clients in the US and Europe.”

Explore sample resumes

Explore these effective resume examples to guide your focus and priorities during the candidate review.

• AI Developer Resume Sample
• AI Scientist Resume Sample

Contact DevsData LLC

If you’re looking to hire a qualified Interim Recruiter, reach out to DevsData LLC at general@devsdata.com or visit www.devsdata.com. The company’s recruitment process is thorough and efficient, utilizing a vast database of over 65000 professionals.

They are renowned for their rigorous 90-minute interviews to assess candidates’ technical skills and problem-solving abilities.

Additionally, DevsData LLC holds a government-approved recruitment license, ensuring compliance with industry standards and regulations.