Senior Machine Learning Engineer

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The Information Technology team has the mission of becoming a true business partner and we are searching for a Senior Machine Learning Engineer to help execute on this mission. The Senior Machine Learning Engineer will work on building end to end AI solutions leveraging proprietary and 3rd party data sources that drive business growth and achieve productivity gains. Ideal candidates love breaking down problems, building solutions, delivering actionable and data-driven insights, and working in a fast-paced, dynamic environment. This role is pivotal, stretching beyond these responsibilities, ensuring AI/ML's transformative potential is realized across our enterprise.

Responsibilities May Include But Are Not Limited To:

• Design, develop, productionize and operate Machine learning models, including Large-Language-Models, and pipelines at scale, for both batch and real-time use cases.
• Drive broad spectrum of tasks such as designing system and model architectures, conducting rigorous experimentation and model evaluations.
• Collaborate with machine learning infrastructure engineers to evolve how we build reusable and scalable AI solutions.
• Analyze structured and unstructured data to understand how our customers interact with our product and service offerings.
• Perform the design, analysis, and interpretation of projects from data requirement gathering to data processing, modeling, and recommendations.
• Leverage third-party and in-house Machine Learning tools & infrastructure to develop reusable, highly differentiating and high-performing machine learning systems, enable fast model development, low-latency serving and ease of model quality upkeep.
• Work collaboratively with cross-functional partners including product owners, operations, legal, and data scientists, identify opportunities for business impact, understand and prioritize requirements for machine learning systems and data pipelines, drive engineering decisions and quantify impact.

Qualifications:

• Master or PhD in a quantitative subject (Statistics, Mathematics, Computer Science, Operations Research).
• 5+ years of industry experience in the applied machine learning domain.
• Expertise in Python with and the ability to write performant production-quality code, familiarity with SQL, knowledge of Spark and cloud data environments (e.g. Azure, Databricks).
• Experience building and scaling machine learning models in business applications using large amounts of data.
• Industry experience building end-to-end Machine Learning infrastructure and/or building and productionizing Machine Learning models.
• Hands on experience with deep learning frameworks (e.g. PyTorch, TensorFlow) and GenAI models (e.g. GPT, StableDiffusion).
• Exposure to architectural patterns of large, high-scale software applications (e.g., well-designed APIs, high volume data pipelines, efficient algorithms, models).
• Experience managing and optimizing Azure cloud data technologies (Synapse, Databricks, ADF, or Azure Data Lake).
• Focus on business practicality and the 80/20 rule; very high bar for output quality, but recognize the business benefit of "having something now" vs "perfection sometime in the future."
• Agile development mindset, appreciating the benefit of constant iteration and improvement.
• Self-starter, comfortable with ambiguity, ability to initiate and drive projects with minimal oversight and guidance.
• A record of continuous learning and adaptation to stay updated with the latest in machine learning, generative AI, cloud technologies, and data compliance standards.
• Experience with Enterprise Search, Information Extraction, Recommendation Systems, Knowledge Graph, Natural Language Processing, Computer Vision techniques.
• 2 years of experience working in a complex, matrixed organization involving cross-functional, and/or cross-business projects.
• Experience in the investment banking or financial sector.

William Blair is an equal opportunity employer. It complies with all laws and regulations that prohibit discrimination in employment practice because of race, color, religion, creed, ancestry, marital status, gender, age, national origin, sexual orientation, unfavorable discharge from the military service or on the basis of a physical or mental disability that is unrelated to the employee's ability to perform the duties of the job applied for. EOE m/f/d/v

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