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ML Lead Engineer - Cincinnati, United States - Tech Mahindra Limited
Description
Role:
ML Lead Engineer
Location:
Cincinnati, OH
Technical Skills and Expertise
Machine Learning Proficiency:
Strong understanding of machine learning algorithms and principles, especially those relevant to anomaly detection, such as supervised and unsupervised learning, clustering, and neural networks.
Data Handling:
Expertise in managing, processing, and analyzing large datasets. Familiarity with data cleaning, data transformation, and feature engineering is crucial.
Programming Skills:
Proficiency in programming languages commonly used in machine learning such as Python.
Model Development and Evaluation:
Ability to develop robust ML models and evaluate their performance through metrics specific to anomaly detection.
System Integration:
Skills to integrate ML models into existing systems for seamless data flow and model deployment including Azure big data and analytics experience.
Lead Experience: 2 – 3 years of experience leading development teamsProblem-Solving Skills
Analytical Thinking:
Ability to analyze complex data and identify patterns or inconsistencies that may indicate problems.
Creative Problem Solving:
Capacity to devise innovative solutions that improve detection and prediction of anomalies.
Attention to Detail:
Precision in model tuning and the interpretation of data to ensure high accuracy and reliability of outputs.
Communication and Collaboration
Clear Communication:
Ability to explain complex ML concepts and findings to non-technical stakeholders.
Collaborative Spirit:
Willingness to work closely with IT teams, data scientists, and other departments to ensure models align with broader business objectives.
Tech Mahindra is an Equal Employment Opportunity employer. We promote and support a diverse workforce at all levels of the company.All qualified applicants will receive consideration for employment without regard to race, religion, color, sex, age, national origin or disability.
All applicants will be evaluated solely on the basis of their ability, competence, and performance of the essential functions of their positions