AI / ML Engineering Senior Manager

Bamboohr

Full-time - Senior

Onsite

Publishing Industries

About the position

The AI / ML Engineering Senior Manager at BambooHR will play a crucial role in expanding the company's AI capabilities within its product and platform. This position involves managing a team of data scientists, machine learning engineers, and software engineers to develop AI-powered applications and enhance platform components. The ideal candidate will demonstrate leadership, provide technical guidance, and foster a culture of continuous learning and innovation while collaborating with various stakeholders to deliver AI-enabled software solutions.

Responsibilities

• Manage data scientists, machine learning engineers, and software engineers building AI-powered applications and key platform components
• Demonstrate leadership and patience through regular coaching and mentoring in individual and team settings
• Provide technical guidance and foster a culture of continuous learning and innovation
• Consult with product management, UX designers, tech leads and business stakeholders to explore and deliver AI-enabled software solutions and platform capabilities
• Oversee the development and deployment of machine learning models, algorithms, and intelligent services to extract insights and create value for customers and the business
• Ensure the quality, accuracy, and reliability of data science and AI applications through rigorous testing, validation, and monitoring
• Collaborate with IT teams to ensure availability, scalability, and security
• Manage and maintain your team's execution roadmap, including grooming a pipeline and delivery expectations
• Show and maintain accountability in team and individual performance in research and development efforts, project delivery goals, and OKRs
• Participate in department hiring efforts
• Contribute to the ongoing improvement of our systems and processes
• Stay up-to-date with relevant advancements and evaluate their potential application
• Be a strong culture addition and advocate for our company values

Requirements

• 12+ years of experience deriving insights from data and building computational software (data science, machine learning, AI, and implementing data-centric software and systems)
• 5+ years of real-world, demonstrable technical leadership
• Strong technical foundations in wielding data (data querying / transformation / visualization, machine learning, deep learning, stats, math, NLP, generative AI and LLMs)
• Demonstrated architecture experience
• Proficiency in git-based workflows with AI and machine learning tools
• Analytical and problem-solving skills, with the ability to translate business requirements into technical solutions
• Exceptional interpersonal and communication skills, distilling complex technical concepts and insights
• Leadership and project management skills to prioritize tasks, manage resources, and meet deadlines

Nice-to-haves

• Proficiency in documenting processes and monitoring performance metrics
• Demonstrated experience delivering machine learning projects, and scaling data solutions and intelligent applications
• Development expertise in languages and tools such as Python, Clojure, SQL, LLMs, Spark, and data science libraries and frameworks (TensorFlow, PyTorch, scikit-learn)
• Solid understanding of data engineering principles, data management, and data governance
• Skill with analytical data stores such as Snowflake, Databricks, and in-house application data
• Experience deploying and maintaining production AI applications in cloud environments, ideally in support of continuously deployed SaaS applications
• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field. PhD is a plus.

Benefits

• 4 weeks paid time off
• 11 paid holidays
• Health Medical with HSA and FSA options, dental, and vision
• 401(k) with a generous company match
• Access to a personal financial planner
• Legal and life insurance
• Financial Peace University
• Paid time to give back to the community
• Educational expense coverage
• In-person onboarding class at Draper, UT headquarters
• Flexible work models (in-office, work-from-home, or hybrid)