Note: The job is a remote job and is open to candidates in USA. Arkhya Tech. Inc. is seeking an experienced Technical Project Manager to lead enterprise AI/ML and MLOps initiatives. The role oversees end-to-end AI/ML program delivery, lifecycle management, platform operationalization, governance, metrics, cross-functional coordination, and continuous improvement across engineering, data science, cloud, product, security, compliance, and business teams.
Responsibilities
- Lead end-to-end delivery of AI/ML and MLOps programs, including roadmap planning, project execution, stakeholder management, risk mitigation, resource planning, governance, and executive reporting
- Manage the complete AI/ML lifecycle, including data preparation, feature engineering, model training, validation, fine-tuning, deployment, monitoring, retraining, and model retirement
- Drive adoption and operationalization of MLOps platforms, establishing robust CI/CD pipelines, automated model deployment, version control, model governance, and production-readiness processes
- Define, track, and communicate AI/ML success metrics, including accuracy, precision, recall, F1 score, latency, throughput, model drift, explainability, model health, and business outcomes
- Partner with Data Scientists, ML Engineers, Software Engineers, DevOps, and Cloud Engineering teams to accelerate model deployment, resolve production issues, and improve the reliability, scalability, and performance of AI/ML solutions
- Provide technical leadership based on strong software development and architecture experience, with an understanding of application architectures, APIs, microservices, cloud platforms, data pipelines, integration patterns, and distributed systems
- Coordinate cross-functional teams and dependencies to ensure successful delivery of AI/ML platform and application initiatives
- Establish project plans, milestones, dependencies, delivery metrics, and risk-management strategies across multiple concurrent initiatives
- Drive AI governance, compliance, security, and responsible AI practices, ensuring appropriate model oversight, observability, operational excellence, and continuous improvement
- Facilitate Agile/Scrum ceremonies, technical discussions, status reviews, executive updates, and stakeholder communications
- Identify opportunities to improve automation, platform capabilities, engineering processes, and overall AI/ML delivery efficiency
Skills
- 10–15 years of overall IT experience, including at least 5 years of Technical Project, Program, or Delivery Management experience
- Strong software development background with .NET and/or Java
- Solid understanding of Machine Learning, MLOps, Generative AI, Large Language Models (LLMs), model deployment, fine-tuning, and model evaluation
- Experience with cloud platforms such as AWS, Azure, and/or Google Cloud Platform (GCP)
- Familiarity with ML and MLOps platforms and technologies such as MLflow, Amazon SageMaker, Vertex AI, Kubernetes, Docker, and CI/CD pipelines
- Understanding of data engineering, APIs, microservices, cloud-native architectures, and enterprise integration patterns
- Experience working with model monitoring, observability, governance, versioning, and production support processes
- Strong communication, stakeholder management, problem-solving, and technical leadership skills
- Proven ability to work effectively across Data Science, Engineering, Product, Cloud, Security, Compliance, and Business teams
- Experience working in Agile/Scrum delivery environments
- Ability to translate complex technical concepts into clear business and executive-level communication
Benefits
- Remote work arrangement
Company Overview
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