Senior Technical Project Manager

Who are Inference Group? Are you ready to be a part of a company that’s redefining the future of data and AI? Welcome to Inference Group, where we’re not just a tech startup – we’re a team of passionate innovators dedicated to empowering businesses through the transformative power of data, machine learning, and AI. At Inference Group, we’re on a mission to help businesses unlock their true potential and drive sustainable growth. As we rapidly expand, we’re looking for like-minded, creative technical experts who want to make a real impact. Here, you’ll work alongside leading experts in data, AI, and technology, guiding clients to harness the full potential of their data.

We believe in making the most out of our journey. If you’re ambitious, innovative, and eager to contribute to the early stages of a dynamic consultancy, we’d love to have you on board. Together, we’ll explore the limitless opportunities of data and AI, driving excellence and having a lot of fun along the way. Join us and be a part of something extraordinary.

We are seeking an experienced Senior Technical Project Manager to lead the delivery of complex data science, machine learning, and analytics projects for our clients. In this role, you will orchestrate cross-functional teams to build and deploy technical solutions at scale. You will be the on point person ensuring projects are delivered on time and within scope, all while managing technical risks and keeping stakeholders (both internal and client-side) fully engaged. This is a high-impact, client-facing role suited for a candidate with a consulting mindset who can balance technical depth with business acumen. If you have a passion for translating innovative AI ideas into real-world solutions and excel at guiding teams through delivery complexity, we want to hear from you.

Your key responsibilities will be:

• Lead end-to-end project delivery: Plan, execute, and oversee data and AI projects from inception through production deployment. Ensure project goals, scope, and timelines are clearly defined and met.
• Coordinate cross-functional teams: Manage and align the efforts of data scientists, ML engineers, data engineers, cloud architects, and business analysts. Foster teamwork and clear communication among diverse technical and non-technical members to achieve shared objectives.
• Client and stakeholder management: Serve as the primary liaison for client stakeholders, building trust and managing expectations. Translate business requirements into technical tasks and ensure the delivered solution addresses the client’s needs.
• Leverage cloud and MLOps best practices: Guide teams in architecting and implementing solutions on GCP (and other cloud platforms as needed), utilizing services and tools (e.g. BigQuery, Vertex AI, Cloud Storage) to ensure scalability and reliability. Champion MLOps practices such as CI/CD pipelines for ML, automated testing, and model monitoring to enable robust, sustainable deployments.
• Risk management and problem-solving: Proactively identify and mitigate technical risks and blockers throughout the project lifecycle. For example, anticipate challenges like data quality issues, model performance shortfalls, or integration hurdles with legacy systems, and develop contingency plans to address them.
• Agile project governance: Apply appropriate project management methodologies (Agile/Scrum or hybrid approaches) to track progress and adapt to changes. Run sprint planning, stand-ups, and retrospectives when applicable, and maintain project tracking tools (e.g. JIRA or similar) for transparency.
• Ensure delivery excellence: Uphold high standards for project deliverables and outcomes. This includes reviewing work to ensure it meets quality expectations, aligns with the solution architecture, and complies with any regulatory or security requirements. Drive continuous improvement by capturing lessons learned and best practices for future projects.
• Mentorship and leadership: Provide guidance and mentorship to team members. Help develop junior project managers or coordinators, share knowledge of AI project delivery, and contribute to a culture of learning and innovation within Inference Group.
• Support growth and innovation: Work closely with account directors and the sales team in scoping new engagements, contributing to proposals, and identifying opportunities to expand our work with existing clients. Bring a consulting perspective to suggest innovative solutions and ensure client satisfaction, potentially leading to repeat business.

This role provides a unique opportunity for a proactive and driven individual to take their consulting career to the next level. We are looking for applicants who have:

• Proven Project Management Experience: 7+ years of experience managing technology projects (with at least 3+ years specifically leading data science, machine learning, or advanced analytics initiatives). Demonstrated success in delivering complex projects on schedule and within budget.
• Technical Background in Data/AI: Strong understanding of the data science lifecycle and machine learning concepts. While you don’t need to be an ML developer, you should be comfortable discussing model training, data pipelines, and deployment workflows with technical experts.
• Cloud Expertise: Hands-on experience delivering projects on cloud platforms, such as Google Cloud Platform. Familiarity with GCP’s data and ML ecosystem (BigQuery, Dataflow, Vertex AI, etc.) is a big plus. Experience with other cloud platforms (AWS/Azure) and hybrid cloud environments is beneficial.
• MLOps and Data Engineering Knowledge: Working knowledge of MLOps practices and tools – e.g., version control for data/models, CI/CD for machine learning, containerization (Docker, Kubernetes), and pipeline orchestration. Understanding of data engineering principles (ETL/ELT processes, data warehousing) to oversee data pipeline development.
• Leadership and Team Management: Excellent leadership skills with a track record of leading cross-functional teams of 5-15+ members. Ability to motivate team members, resolve conflicts, and make informed decisions to keep the project moving forward.
• Agile and Project Process Skills: Proficiency in project management methodologies (Scrum/Agile, Kanban, and traditional project management as needed). Capable of tailoring your approach to suit project and client context. Certification such as PMP, PRINCE2, or Agile/Scrum Master is a plus, but proven skills are most important.
• Stakeholder Engagement: Exceptional communication and interpersonal skills. Able to interface effectively with both technical teams and C-level/business stakeholders. Experience in a client-facing role or consulting environment is highly valued – you can manage client expectations, conduct presentations or demos, and ensure stakeholder buy-in at various project stages.
• Problem-Solving and Adaptability: Adept at analytical thinking and creative problem-solving. Comfortable dealing with ambiguity and rapidly changing requirements. You should be able to prioritize tasks, manage multiple workstreams, and adjust plans when new challenges arise.
• Educational Background: Bachelor’s or Master’s degree in a relevant field (Computer Science, Data Science, Engineering, Information Systems, or similar). Equivalent work experience in managing technical projects will also be considered. Continuous learning (through courses, certifications, staying up-to-date with industry trends) is expected.

We are looking for dedicated people who are both passionate about project delivery and technology while having the empathy to succeed in client consulting.

Preferred Qualifications

• Consulting Experience: Prior experience in a consulting firm or managing projects for external clients. Understanding of the dynamics of consulting engagements, including scope management and delivering under defined contracts/SoWs.
• Advanced Cloud & Data Certs: Certifications such as Google Professional Cloud Architect or Machine Learning Engineer, or similar certifications on AWS/Azure, demonstrating depth of cloud knowledge. Project management certifications (PMP, PMI-ACP, etc.) are nice to have as well.
• Domain Knowledge: Experience with data privacy, governance, and compliance aspects in AI projects (e.g., handling sensitive data, model bias/fairness considerations). Any domain-specific expertise (e.g., in retail, finance, supply chain analytics) that can help contextualize AI solutions for clients is a plus.
• Tooling and Tech: Familiarity with tools and platforms commonly used in data & AI projects, such as: version control (Git), collaboration tools (Confluence, Slack), ML lifecycle tools (MLflow, Kubeflow), and DevOps infrastructure (CI/CD pipelines, Terraform for infrastructure-as-code on cloud).
• Big Data & Analytics: Experience with big data technologies (Spark, Hadoop) or real-time data streaming (Kafka) in the context of analytics projects. This demonstrates ability to manage projects dealing with large-scale data and high-throughput systems.
• Entrepreneurial Mindset: A proactive, self-starter attitude that fits a scale-up culture. Willingness to take ownership beyond the job description, contribute ideas to improve our services, and adapt to the evolving needs of a growing company.

We are a young small company, growing quickly and are looking to hire people at this stage who will be our future leaders. We have access to the latest technology, and will provide training in these and certifications to help you grow, this is a rapidly changing environment and we want our clients to know that we have the most up to date skills and experience to help them deliver. If you like our mission, if you support our values, we encourage you to apply.