AI/ML Architect

Synechron; Las Vegas (NV); On-site; USD 140,000 - 160,000; Full time

Benefits offered by this job

Flexible hybrid policy

Paid time off (leave)

Healthcare benefits

Professional development

Job summary

Synechron is seeking an experienced AI/ML Architect to design, develop, and lead scalable AI/ML solutions across enterprise environments. You will set architecture standards, guide model development, and collaborate with stakeholders to deliver measurable business value.

The role requires deep expertise in ML, software engineering, cloud platforms, MLOps, data architecture, and governance. Strong leadership and communication skills are essential.

Qualifications

• Bachelor's or master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, or related discipline.
• 12+ years of experience in software engineering, data science, ML, or technology architecture.
• 5+ years designing and implementing enterprise AI/ML solutions.
• Strong hands-on experience with ML algorithms, deep learning, model development, and deployment.
• Experience designing production-grade AI/ML platforms and systems.
• Strong programming skills in Python and familiarity with Java/Scala/SQL.
• Experience with ML frameworks such as PyTorch, TensorFlow, Scikit-learn, XGBoost, Hugging Face Transformers.
• Experience with cloud platforms such as AWS, Azure, Google Cloud.
• Practical knowledge of MLOps tools and practices.
• Experience with data platforms, APIs, databases, data warehouses and data lakes.
• Strong understanding of distributed systems, microservices, containers and Kubernetes.
• Experience with CI/CD, infrastructure automation, observability and system monitoring.

Responsibilities

• Define the end-to-end architecture for AI, machine learning, deep learning, and generative AI solutions.
• Design scalable, reliable, secure, and cost-effective AI/ML platforms and applications.
• Evaluate and recommend models, algorithms, frameworks, tools, and technologies.
• Establish architectural standards, design principles, reusable components, and best practices.
• Create architecture diagrams, technical specifications, proof-of-concept designs, and roadmaps.
• Ensure AI/ML solutions integrate with existing enterprise systems and applications.
• Guide design and development of predictive, prescriptive, and classification models.
• Lead NLP, computer vision, recommendation, forecasting, and optimization solutions.
• Design and oversee generative AI applications, including LLMs, RAG, prompts, fine-tuning, AI agents.
• Define strategies for training, validation, deployment and monitoring of models.
• Ensure models are accurate, explainable, and maintainable.

Skills

AI/ML architecture

Software engineering

Cloud platforms

Data architecture

MLOps

Education

Degree in CS/AI/DS/Engineering

Tools

Python

Java/Scala/SQL

PyTorch

TensorFlow

Scikit-learn

XGBoost

Hugging Face Transformers

AWS/Azure/GCP

Job description

At Synechron, we believe in the power of digital to transform businesses for the better. Our global consulting firm combines creativity and innovative technology to deliver industry-leading digital solutions. Synechron’s progressive technologies and optimization strategies span end-to-end Artificial Intelligence, Consulting, Digital, Cloud & DevOps, Data, and Software Engineering, servicing an array of noteworthy financial services and technology firms. Through research and development initiatives in our FinLabs we develop solutions for modernization, from Artificial Intelligence and Blockchain to Data Science models, Digital Underwriting, mobile-first applications and more. Over the last 20+ years, our company has been honored with multiple employer awards, recognizing our commitment to our talented teams. With top clients to boast about, Synechron has a global workforce of 17000+, and has 58 offices in 22 countries within key global markets.

We are seeking an experienced AI/ML Architect to design, develop, and lead the implementation of scalable, secure, and production-ready artificial intelligence and machine learning solutions. The successful candidate will define the organization’s AI/ML architecture, establish engineering standards, guide model development and deployment, and collaborate with business and technology stakeholders to deliver measurable value.

This role requires a strong combination of expertise in machine learning, software engineering, cloud platforms, data architecture, MLOps, and enterprise solution design.

Additional Information*

The base salary for this position will vary based on geography and other factors. In accordance with law, the base salary for this role if filled within Las Vegas, NV is $1400K - $160K & benefits (see below).

The Role

Responsibilities

• Define the end-to-end architecture for AI, machine learning, deep learning, and generative AI solutions.
• Design scalable, reliable, secure, and cost-effective AI/ML platforms and applications.
• Evaluate and recommend appropriate models, algorithms, frameworks, tools, and technologies.
• Establish architectural standards, design principles, reusable components, and best practices.
• Create architecture diagrams, technical specifications, proof-of-concept designs, and implementation roadmaps.
• Ensure AI/ML solutions integrate effectively with existing enterprise systems and applications.

Machine Learning and Generative AI

• Guide the design and development of predictive, prescriptive, and classification models.
• Lead the implementation of natural language processing, computer vision, recommendation systems, forecasting, and optimization solutions.
• Design and oversee generative AI applications, including large language model integrations, retrieval-augmented generation, prompt engineering, fine-tuning, and AI agents.
• Define strategies for model training, validation, evaluation, versioning, deployment, and monitoring.
• Ensure models are accurate, explainable, maintainable, and fit for business use.

MLOps and Platform Engineering

• Design and implement robust MLOps practices and pipelines.
• Establish processes for continuous integration, continuous delivery, model deployment, monitoring, retraining, and rollback.
• Implement model and data versioning, experiment tracking, feature stores, model registries, and automated testing.
• Develop solutions for real-time, batch, and streaming inference.
• Ensure production systems meet performance, availability, scalability, and reliability requirements.

Data and Cloud Architecture

• Collaborate with data engineering teams to design secure and efficient data pipelines and platforms.
• Define data requirements, feature engineering strategies, data quality standards, and governance processes.
• Design AI/ML solutions using cloud platforms such as AWS, Microsoft Azure, or Google Cloud.
• Leverage cloud-native services, distributed computing, containers, Kubernetes, APIs, and serverless technologies where appropriate.
• Optimize infrastructure utilization and cloud costs.

Governance, Security, and Responsible AI

• Establish standards for AI governance, model risk management, data privacy, and responsible AI.
• Address bias, fairness, transparency, interpretability, security, and ethical considerations in AI/ML solutions.
• Ensure compliance with applicable regulations, organizational policies, and industry standards.
• Design secure AI systems that protect sensitive data, models, prompts, and intellectual property.
• Define controls for model access, auditability, data lineage, and usage monitoring.

Leadership and Collaboration

• Provide technical leadership and mentorship to data scientists, ML engineers, software engineers, and data engineers.
• Partner with product managers, business leaders, architects, security teams, and other stakeholders.
• Translate business requirements into practical AI/ML solutions and technical roadmaps.
• Review designs, code, models, and deployment strategies.
• Lead technical discussions, architecture reviews, and implementation workshops.
• Stay current with emerging AI/ML technologies, research, tools, and industry trends.

Requirements

Bachelor's or master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, or a related discipline.

12+ years of experience in software engineering, data science, machine learning, or technology architecture.

5+ years of experience designing and implementing enterprise AI/ML solutions.

Strong hands-on experience with machine learning algorithms, deep learning, model development, and deployment.

Experience designing production-grade AI/ML platforms and systems.

Strong programming skills in Python and familiarity with languages such as Java, Scala, or SQL.

Experience with machine learning frameworks such as:

• PyTorch
• TensorFlow
• Scikit-learn
• XGBoost
• Hugging Face Transformers

Experience with cloud platforms such as AWS, Azure, or Google Cloud.

Practical knowledge of MLOps tools and practices.

Experience with data platforms, APIs, databases, data warehouses, and data lakes.

Strong understanding of distributed systems, microservices, containers, and Kubernetes.

Experience with CI/CD, infrastructure automation, observability, and system monitoring.

Excellent communication, problem-solving, and stakeholder-management skills.

Preferred skills

• Drive results to achieve high-quality work results regardless of work complexity.
• Build collaborative relationships both internally and externally
• Decision making to identify and understand situations; identify opportunities to proactively resolve.
• Personal energy to proactively address situations and adopt a positive approach, resilience in front of change and obstacles.
• Self-leadership to continuously learn and develop oneself
• Foster innovation

We offer

• A multinational organization with 58 offices in 22 countries and the possibility to work abroad.
• 10 days of paid annual leave plus an additional 10 days of personal leave (floating days and sick days).
• A comprehensive insurance plan including medical, dental, vision, life insurance, and long-term disability.
• Flexible hybrid policy.
• RRSP with employer's contribution up to 4%.
• A higher education certification policy.
• On-demand Udemy for Business for all Synechron employees with free access to more than 5000 curated courses.
• Coaching opportunities with experienced colleagues from our Financial Innovation Labs (FinLabs) and Center of Excellences (CoE) groups.
• Cutting edge projects at the world's leading tier-one banks, financial institutions and insurance firms.
• A truly diverse, fun-loving and global work culture.

S YNECHRON'S DIVERSITY & INCLUSION STATEMENT

Diversity & Inclusion are fundamental to our culture, and Synechron is proud to be an equal opportunity workplace and is an affirmative action employer. Our Diversity, Equity, and Inclusion (DEI) initiative 'Same Difference' is committed to fostering an inclusive culture - promoting equality, diversity and an environment that is respectful to all. We strongly believe that a diverse workforce helps build stronger, successful businesses as a global company. We encourage applicants from across diverse backgrounds, race, ethnicities, religion, age, marital status, gender, sexual orientations, or disabilities to apply. We empower our global workforce by offering flexible workplace arrangements, mentoring, internal mobility, learning and development programs, and more.

All employment decisions at Synechron are based on business needs, job requirements and individual qualifications, without regard to the applicant's gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law.