Manager, Software Engineering (AI/ML)

About the Role

Key Responsibilities

• Establish methodologies for quickly rolling out new data analysis capabilities for standalone data-driven products and services to support associates using AI, ML, and LLMs.
• Lead architecture and technical design discussions to ensure data science solutions align with the organization's strategic objectives.
• Continuously improve models through experimentation and optimization techniques.
• Analyze unstructured text data to discover insights and patterns using advanced data science techniques, including machine learning and natural language processing.
• Use a combination of quantitative (science) and qualitative (art) methodologies to prioritize AI initiatives.
• Stay on top of fast-moving AI/ML models and technologies, understand and follow disruptive data science solutions, evangelize new technologies, and drive their adoption.
• Create Data Science packages and APIs for use across the organization.
• Mentor junior team members on effective technical practices and non-technical skills.
• Be accountable for the scalability, stability, and business adoption of data science solutions.
• Manage formal and informal project communication amongst team and with other project participants using appropriate methods.
• Evaluate developers after project completion, identifying strengths and areas for development.

Requirements

• 6+ years of experience in algorithms, statistics, data mining, machine learning, deep learning, and natural language processing.
• Ability to provision packages and APIs for production data science code.
• Education qualification as graduate or postgraduate degree in Engineering or Data Science.
• Experience in machine learning models and techniques like NLP, BERT, Transformers, Deep learning.
• Experience using LLMs (e.g., OpenAI, Cohere, Anthropic, Llama, etc) to deliver business outcomes.
• Ability to translate quantitative analysis into actionable business strategies.
• Ability to work collaboratively across business, data science, and technical stakeholders.
• Experience in coaching/mentoring junior associates.

Nice to Have

• Experience building scalable data models and performing complex relational database queries using SQL (Oracle, MySQL, PostgreSQL).
• Knowledge of MLOps frameworks like Kubeflow, MLFlow, DataRobot, Airflow.
• Knowledge of AWS tools such as Sagemaker, Lambda, EKS.

Qualifications

• Graduate or postgraduate degree in Engineering or Data Science.

Benefits & Perks

• Competitive compensation.
• Limitless growth and learning opportunities.
• Ongoing mentorship, leadership courses, development programs, technical courses, certification opportunities.
• A collaborative and positive culture with a diverse team.
• Flexible work environment with remote and on-site options.
• 20+ PTO days plus holidays and floating holidays in the first year.
• Extensive medical, dental, and vision insurance.
• 401K with corporate match, immediate vesting.
• Health-and-wellness-related allowance programs.
• Parental leave.
• Tuition reimbursement.
• Employee Stock Purchase Plan.
• Employee Assistance Program.
• Gartner Gives Charity Match.