Senior Machine Learning Engineer

Key Responsibilities:

• Identify high-impact business opportunities and define data science strategies to address them.
• Translate ambiguous product or business problems into structured, solvable machine learning challenges.
• Design and implement robust ML models, focusing on measurable business outcomes and model

interpretability.

• Drive collaboration with engineering and product teams to ensure successful, scalable deployment of ML

solutions in production.

• Set up monitoring systems for live models, including real-time tracking of data drift, performance degradation,

and failure modes.

• Promote engineering excellence and knowledge-sharing by mentoring junior team members and setting teamwide best practices.
• Present data-driven insights and model results clearly and effectively to influence product strategy and

stakeholder alignment.

What Were Looking For:

• 3+ years of hands-on experience in Data Science and Machine Learning, including real-world model deployment.
• Strong technical expertise in NLP, Deep Learning, Ranking Algorithms, and Ensemble Methods.
• Proficient in Python with strong engineering discipline and experience in scalable model development.
• Experience with ML deployment frameworks (e.g., Snowpark, MLflow) and production environments.
• Familiarity with modern ML libraries and frameworks such as PyTorch or TensorFlow.
• Skilled in SQL and comfortable working with large-scale structured datasets.
• Academic background in Engineering, Statistics, Computer Science, or related disciplines.
• Strong business acumen, excellent communication skills, and a scientific, data-driven mindset.
• Exposure to cloud platforms like GCP and warehouse like Snowflake is an added advantage.