Senior Machine Learning Engineer | $210k-$230k | Hybrid | New York, NY

$210,000 - $230,000/Yr

Société Liégeoise d'Etudes et de Réalisations Esthétiques - New York, NY

Full-time - Senior

New York, NY

About the position

The Senior Machine Learning Engineer will play a pivotal role in guiding and influencing multiple teams within the organization, focusing on the strategic vision for the development and integration of machine learning technologies. This position is crucial for driving innovation, mentoring engineers, and ensuring alignment with the organization's broader goals, all while contributing to the mission of improving the lives of injured and disabled workers.

Responsibilities

• Amplify the influence of machine learning solutions across various teams.
• Develop and implement strategic ML initiatives that support organizational goals.
• Lead the design and deployment of advanced ML systems to enhance product offerings.
• Ensure alignment and knowledge sharing across the department for all ML efforts.
• Drive the department-wide adoption of cutting-edge machine learning techniques and frameworks.
• Lead impactful projects that use ML to create new market opportunities and enhance the competitive edge.
• Promote collaboration among different teams for seamless integration of ML technologies.
• Guide the creation of scalable and robust ML architectures that underpin multiple product applications.
• Foster a culture of continuous learning and adaptability to new ML technologies and market trends.

Requirements

• Over 8 years of experience as an ML Engineer or Data Scientist, ideally in SaaS environments.
• Proficient in identifying and translating client business problems into ML solutions, demonstrating their business impact.
• Strong written and verbal communication skills.
• Skilled in modelling dynamic systems and time series forecasting.
• Extensive experience with ML technology stack, including Python/Pandas, Pytorch, Sklearn, Keras/TensorFlow tuning frameworks, and scalable technical solutions.
• Proficient in analytical and statistical modeling, such as non-parametric prediction, unsupervised learning, measuring uncertainty, and statistical inference.
• Active in the open-source community with contributions to public libraries or frameworks.

Nice-to-haves

• Formal training in various statistical learning algorithms.
• Over 5 years of experience deploying ML systems on platforms like GCP or AWS.
• Experience in managing model serving pipelines in production environments.
• Creative and resourceful problem-solving skills.
• Values ambition, collaboration, and empathy.
• Experience with probabilistic programming.

Benefits

• Equity
• Bonus
• Comprehensive benefits package