Agile Project Manager – ML

Gravity IT Resources; Atlanta (GA); On-site; USD 85,000 - 130,000; Full time

Job summary

An innovative firm is seeking a skilled Agile Project Manager with a strong foundation in machine learning to lead dynamic teams on groundbreaking projects. This role involves overseeing the successful delivery of ML solutions while ensuring adherence to Agile best practices. You'll collaborate with data scientists and engineers, manage project backlogs, and communicate effectively with stakeholders to align on project goals. If you're passionate about technology and thrive in a fast-paced environment, this position offers a unique opportunity to make a significant impact in the field of machine learning.

Qualifications

• 5+ years of Agile Project Management experience in tech-driven projects.
• Solid understanding of machine learning concepts and methodologies.
• Ability to communicate complex technical concepts to non-technical stakeholders.

Responsibilities

• Lead cross-functional teams using Agile methodologies for ML projects.
• Manage multiple ML projects, ensuring quality and timely delivery.
• Act as the primary point of contact for stakeholders on project expectations.

Skills

Agile Project Management

Machine Learning Knowledge

Communication Skills

Problem-Solving Mindset

Education

Bachelor's Degree in Computer Science or related field

Certified Scrum Master (CSM) or Agile PMP Certification

Tools

TensorFlow

PyTorch

scikit-learn

AWS Sagemaker

Google AI

Azure ML

Kubernetes

Job description

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Job Title: Agile Project Manager with Machine Learning Knowledge
About the Role:
We are seeking a talented and driven Agile Project Manager to lead teams working on cutting-edge Machine Learning projects. You will be responsible for overseeing the delivery of ML-based solutions, ensuring that our agile teams adhere to best practices, and that we meet project milestones with high quality and efficiency. This role requires a blend of deep agile project management experience and a strong understanding of machine learning technologies and workflows.
Responsibilities:

• Agile Leadership:Lead, coach, and mentor cross-functional teams using Agile methodologies (Scrum, Kanban, or other frameworks) to ensure the successful and timely delivery of machine learning projects.
• Project Delivery:Manage multiple ML projects simultaneously, ensuring that project goals, timelines, and budgets are met while maintaining a high level of quality.
• Stakeholder Communication:Act as the primary point of contact for both internal and external stakeholders. Ensure alignment on project expectations, scope, and progress.
• Backlog Management:Work closely with Product Owners and technical teams to manage and prioritize the product backlog, ensuring that user stories are well-defined and ready for sprints.
• Risk Management:Identify and mitigate risks related to the ML projects, including dependencies, resources, and technological constraints.
• Collaboration with Data Science and Engineering Teams:Work closely with data scientists, engineers, and other technical resources to ensure alignment between project requirements and the execution of ML algorithms/models.
• Quality Assurance:Ensure that the machine learning models are developed and tested with high-quality standards, including model performance evaluation, accuracy, and robustness.
• Data Management:Ensure that data handling (cleaning, labeling, preprocessing) and model training processes follow best practices and are well understood by all team members.

Qualifications:

• Experience in Agile Project Management:Minimum 5+ years of experience in agile project management, particularly in delivering technology-driven projects using Agile frameworks (Scrum, Kanban, etc.).
• Machine Learning Knowledge:Solid understanding of machine learning concepts, methodologies, and platforms (e.g., TensorFlow, PyTorch, scikit-learn, etc.).
• Technical Understanding of ML Pipelines:Familiarity with the end-to-end machine learning pipeline, including data collection, feature engineering, model training, model evaluation, and deployment.
• Experience with ML Deployment Platforms:Exposure to ML platforms and tools (e.g., AWS Sagemaker, Google AI, Azure ML, Kubernetes for ML deployments).
• Excellent Communication Skills:Proven ability to communicate complex technical concepts to non-technical stakeholders and facilitate clear, concise project updates.
• Problem-Solving Mindset:Ability to anticipate and solve challenges specific to ML project delivery, such as data-related issues, model performance concerns, and resource allocation.
• Certified Scrum Master (CSM) or Agile PMP Certification:Preferred but not required.
• Strong Organizational Skills:Ability to manage multiple priorities, set expectations, and deliver within tight deadlines.

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