Associate AI/ML Engineer

Project Description

The Platform organization is seeking an early-career Associate AI/ML Engineer to support the development, testing, and implementation of practical artificial intelligence and machine learning solutions. This role is designed for a junior engineer with strong fundamentals, curiosity, and the ability to learn quickly in a collaborative engineering environment.

The ideal candidate is coachable, adaptable, execution-oriented, and comfortable communicating progress, questions, and technical concepts clearly. The engineer will work closely with senior engineers, product partners, and data-focused teams to translate defined requirements into reliable, maintainable solutions.

Duties/Day to Day Overview

• Contribute to the design, development, testing, and deployment of AI/ML features and supporting software components under the guidance of senior team members.
• Prepare, clean, transform, and validate data used for model development, experimentation, and evaluation.
• Build and evaluate baseline machine learning models using established techniques and clearly defined success criteria.
• Write clean, maintainable Python code and participate in code reviews, testing, debugging, and documentation.
• Assist with integrating models or AI-enabled capabilities into applications, APIs, workflows, or data pipelines.
• Monitor experiments and model outputs, identify issues, and communicate findings with appropriate context and supporting evidence.
• Break down assigned work into clear tasks, execute reliably, and raise risks or blockers early.
• Collaborate effectively in an Agile engineering team and participate in planning, stand-ups, demos, and retrospectives.
• Quickly learn new tools, concepts, and business context, then apply feedback to improve delivery quality.

Top Requirements (Must Haves)

• Approximately 6-12 months of total professional, internship, co-op, or equivalent hands-on experience in AI/ML, data science, or software engineering is strongly preferred. Candidates with 1-2 years of total experience may be considered; candidates with more than 2 years of total experience will not be considered for this associate-level role.
• Sound understanding of core machine learning concepts, including supervised and unsupervised learning, feature preparation, training and validation, overfitting, and common evaluation metrics.
• Working knowledge of Python and common data or machine learning libraries such as pandas, NumPy, and scikit-learn.
• Basic SQL skills and experience working with structured datasets.
• Foundational knowledge of software engineering practices, including version control, modular code, testing, debugging, and documentation.
• Ability to explain technical work clearly, ask thoughtful questions, and communicate status, decisions, and blockers.
• Demonstrated ability to absorb new concepts quickly, follow through on commitments, and execute with attention to detail.

Preferred Qualifications

• Hands-on academic, internship, or project experience taking an ML use case from data preparation through model evaluation.
• Exposure to deep learning or generative AI concepts, libraries, or APIs.
• Familiarity with cloud platforms, notebooks, containers, REST APIs, or CI/CD practices.
• Experience using Git and collaborating through pull requests or code reviews.
• Awareness of responsible AI practices, including data quality, privacy, bias, explainability, and model limitations.

Success Profile

• Coachable and adaptable: actively seeks feedback and applies it quickly.
• Fast learner: grasps unfamiliar technical and business concepts with limited repetition.
• Execution-oriented: converts direction into completed work and maintains momentum.
• Strong communicator: communicates clearly with both technical and non-technical partners.
• Collaborative and accountable: works well with others, owns deliverables, and escalates blockers promptly.