AI/ML Lead Engineer (Databricks, Azure ML & Python) | SparkTek USA | Dallas, TX

Tech Junction Ltd; Dallas (TX); On-site; USD 180,000 - 240,000; Full time

Job summary

SparkTek USA in Dallas, TX is seeking an AI/ML Lead Engineer to own end-to-end AI architecture, production model deployment, and data governance across multi-cloud platforms (Azure ML, AWS, GCP). You will architect Databricks lakehouse solutions, Unity Catalog, Snowflake, and build scalable Python/SQL pipelines and FastAPI microservices.

Lead with 13+ years of software/AI experience, mentor teams, ensure governance and security, and deliver production-ready ML solutions with robust telemetry and

Qualifications

• Bachelor’s or Master’s degree in relevant technical discipline.
• 13+ years of progressive hands-on software and AI development experience.
• Operational expertise with Databricks lakehouse and Unity Catalog governance.
• Strong Python and SQL coding capabilities for ML pipelines.
• Experience with multi-cloud platforms: Azure ML, AWS, GCP.
• Proficient in FastAPI, data warehousing with Snowflake, and containerization.
• Proven Kubernetes and Docker experience for scalable workloads.
• Authorized to work in Dallas, TX and physically available.

Responsibilities

• Architect, design, develop, test, and deploy enterprise AI/ML solutions.
• Build scalable data lakehouse architectures with Databricks, Unity Catalog, Snowflake.
• Write robust Python/SQL code for AI services and pipelines.
• Develop RESTful microservices using FastAPI.
• Manage multi-cloud ML workloads across Azure, AWS, and GCP.
• Enforce data governance, access controls, and security controls.
• Containerize workloads with Docker and orchestrate with Kubernetes.
• Collaborate with data science, software, and DevOps teams; document runbooks.

Skills

Databricks

Unity Catalog

Python

SQL

Azure ML

AWS

GCP

FastAPI

Docker

Kubernetes

Data governance

Machine Learning

Snowflake

Education

Bachelor’s or Master’s in Computer Science / AI / Data Science

Tools

Databricks

Snowflake

Kubernetes

Docker

Job description

Position Summary

Driving advanced artificial intelligence, machine learning engineering, and large-scale data lakehouse platforms in Dallas, Texas, SparkTek USA is actively seeking an accomplished AI/ML Lead Engineer for a permanent full-time professional engagement. In this vital technical leadership role, you will take full operational, tactical, and technical ownership of Databricks lakehouse architectures, Unity Catalog data governance, multi-cloud ML deployments across Azure ML, AWS, and GCP, robust Python coding, scalable SQL data pipelines, FastAPI microservices, Snowflake data warehousing, and containerized orchestration utilizing Docker and Kubernetes. Bringing 13+ years of progressive professional experience in software engineering and artificial intelligence development, you will empower an elite technology enterprise to achieve uncompromised machine learning performance, secure enterprise AI pipelines, and superior digital enterprise solutions. This prestigious career opportunity offers competitive remuneration, enterprise technology exposure, and professional growth within a leading global IT staffing and software engineering consultancy.

Detailed Job Description

As an AI/ML Lead Engineer supporting SparkTek USA on a professional basis in Dallas, Texas, you will take full operational, tactical, and technical ownership of end-to-end artificial intelligence architecture, production model deployment, data lakehouse governance, high-performance API design, and cross-functional engineering collaboration. Your day-to-day responsibilities include designing, developing, and deploying advanced machine learning models and generative AI solutions into enterprise production environments, architecting scalable data processing pipelines utilizing Databricks, Unity Catalog, and Snowflake, implementing robust data governance and security controls across multi-cloud environments (Azure ML, AWS, and GCP), writing clean, high-performance Python and SQL code for machine learning pipelines and data workflows, building high-throughput FastAPI microservices and RESTful backends, configuring multi-cloud infrastructure and containerized workloads utilizing Docker and Kubernetes, collaborating proactively with data science teams, product owners, and engineering squads, and interacting directly with talent acquisition teams like Sandeep B at SparkTek USA.

Key Responsibilities

• Architect, design, develop, test, and deploy enterprise-grade artificial intelligence and machine learning solutions into live production environments.
• Build and scale advanced data lakehouse architectures utilizing Databricks, Unity Catalog, and Snowflake data warehousing.
• Write robust, highly scalable, and clean Python and SQL code for backend AI services, feature stores, and data processing pipelines.
• Develop high-throughput RESTful microservices and web APIs utilizing FastAPI frameworks.
• Configure, manage, and scale cloud-native machine learning workloads across multi-cloud environments including Azure ML, AWS, and GCP.
• Implement rigorous data governance, access controls, lineage tracking, and security frameworks via Unity Catalog.
• Containerize and orchestrate scalable AI workloads utilizing Docker containerization and Kubernetes cluster management.
• Collaborate proactively with data science, software engineering, and DevOps teams to streamline model deployment and telemetry monitoring.
• Ensure strict adherence to enterprise AI ethics, data security compliance, and model governance standards.
• Maintain meticulous technical documentation, model evaluation reports, API specifications, and infrastructure runbooks.

Required Qualifications & Skills

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related technical discipline.
• Minimum of 13+ years of progressive professional hands‑on software development experience with strong AI and machine learning engineering expertise.
• Strong, demonstrable operational expertise in Databricks architecture, lakehouse implementation, and Unity Catalog data governance.
• Comprehensive working knowledge and practical proficiency in advanced Python coding and SQL database optimization.
• Deep practical experience with multi-cloud machine learning platforms including Azure ML, AWS, and GCP.
• Solid practical grasp of FastAPI microservices development and Snowflake data warehousing.
• Proven hands‑on proficiency in containerization and orchestration utilizing Docker and Kubernetes.
• Mandatory legal work authorization and physical availability for professional operations in Dallas, TX (Local candidates strongly preferred).

Nice-to-Have Skills

• Professional cloud and data certifications such as Databricks Certified Data Engineer Professional or AWS Certified Machine Learning Specialty.
• Prior professional working experience supporting Tier-1 fintech enterprises, healthcare providers, or large-scale digital platforms.
• Hands‑on familiarity with MLOps pipelines (MLflow, Kubeflow) and automated model monitoring tools.
• Experience utilizing enterprise agile tracking and IT service desk platforms (Jira, Confluence, ServiceNow).
• Active participation in artificial intelligence research groups, Databricks user groups, or machine learning forums.

Employment Details

• Salary/Rate: Market Competitive / Enterprise Artificial Intelligence Package
• Work Schedule: Professional Operations (Dallas, TX)
• Deadline: Open until filled (Urgent Dallas AI/ML Lead Engineer Opening)
• Notice Period: Immediate to 30 Days Preferred
• Contract Duration: Permanent / Full-Time Employment

Recruitment Pro Tip

When applying for this AI/ML Lead Engineer position with SparkTek USA in Dallas, ensure your resume explicitly highlights your Databricks/Unity Catalog tenure, multi-cloud ML deployment experience (Azure ML/AWS/GCP), and FastAPI microservices portfolio.