Senior Machine Learning Engineer

The Role:

The Senior Machine Learning Engineer owns the development and deployment of machine learning solutions and influences the technical direction of their team. They will work closely with Product and Engineering partners in the development of the solution.

Responsibilities:

• Lead the development and deployment of Machine Learning solutions to solve business problems.
• Develop and maintain clean, efficient, and scalable code that meets industry standards
• Analyze large datasets to extract actionable insights and make informed decisions.
• Employ state-of-the-art Machine Learning methodologies and frameworks to develop robust and scalable models.
• Influence technical direction and take ownership of key components of systems and solutions, ensuring that they meet the needs of the business.
• Collaborate with key stakeholders in the development of data-driven solutions and deployable products.
• Mentor junior team members to help establish team domain expertise.
• Contribute to the company's intellectual property and technical leadership through patents and publications at top-tier conferences and journals.

Minimum Requirements:

• 5+ years of industry experience in applied Machine Learning
• Masters Degree or PhD in CS / ML or related field 
• 3+ years experience in building, deploying, and managing machine learning and deep learning models in production environments at scale
• Deep understanding of ML best practices (A/B testing, training/serving pipelines, feature engineering etc), algorithms/techniques (gradient boosting, deep neural networks, optimization, regularization), and experiment design
• Experience in at least one of these domains: price estimation, personalization, recommender systems, computer vision, fraud detection and authentication, marketing
• Extensive experience in scientific libraries in Python (numpy, pandas) and Machine
• Learning tools and frameworks (Scikit-Learn, Tensorflow, Keras, PyTorch)
• Strong data engineering skills and experience working with large scale datasets
• Experience with big data tools (Apache Beam, Apache Kafka, Spark)
• Experience with cloud technologies AWS, GCP or Azure
• Fluency in Python, SQL

Preferred Requirements:

• PhD preferred (CS, ML, AI or related field)
• Background in applying ML techniques to solve real-world business problems in the retail sector.
• Familiarity with MLOps tools and pipelines.
• Impact-focused and passionate about delivering high-quality models.
• Demonstrated leadership experience, with the ability to lead and inspire a team.