Machine Learning Engineer
2 weeks ago
Job Summary We are seeking a highly skilled and experienced Machine Learning / AI Engineer to join our dynamic and multicultural environment. The ideal candidate will have a strong foundation in data science, applied machine learning, and MLOps , with the ability to design, build, and deploy end-to-end ML solutions. This role combines technical expertise with cross-functional collaboration to deliver scalable and responsible AI systems aligned with organizational standards and compliance requirements. Job Responsibilities Collaborate with data scientists and business stakeholders to understand use cases and define suitable ML solutions. Design, engineer, and deploy machine learning models into production using MLOps best practices (model versioning, CI/CD, and monitoring). Build and maintain data pipelines and ensure scalability and maintainability of deployed models. Support data exploration, feature engineering, and model development when required. Automate model retraining, testing, and monitoring processes to ensure consistent performance over time. Ensure all ML models comply with Responsible AI standards , governance, and audit requirements. Document ML workflows, governance checkpoints, and risk assessments. Partner with DevOps, IT, and security teams to integrate ML solutions into enterprise systems. Maintain close communication with key stakeholders while demonstrating autonomy and accountability. Job Requirements Mandatory: Master’s degree in Artificial Intelligence, Machine Learning, Data Science, or a related field . 6+ years of experience in data science and machine learning, with at least 3+ years in ML engineering roles. Proven expertise in the end-to-end ML lifecycle — from data preprocessing to deployment and model monitoring. Strong programming skills in Python and familiarity with key ML libraries (pandas, scikit-learn, TensorFlow, PyTorch, etc.). Experience with NoSQL databases (graph database experience is a plus). Proficiency in MLOps tools such as MLflow, TFX, Airflow, or Kubeflow. Hands-on experience with cloud platforms like AWS, Azure, or GCP for ML deployment. Solid understanding of CI/CD pipelines , Docker , and Kubernetes . Strong grasp of AI governance, model risk management , and regulatory compliance for AI solutions. Excellent communication skills with the ability to present technical information to non-technical stakeholders. Preferred: Experience with Responsible AI frameworks and bias/fairness assessment. Knowledge of feature stores , model registries , and data versioning tools . Understanding of data privacy, anonymization , and compliance in regulated environments. Professional Skills and Mindset Strong analytical, problem-solving, and organizational skills. Ability and willingness to learn and adopt emerging technologies . Excellent collaboration and communication skills in a multicultural environment. Awareness of software development methodologies and ability to follow defined processes. Respect for cultural diversity and a commitment to inclusive teamwork. Next Step: If interested, you can click on "Apply here" or write an e-mail to with your updated resume. NOTE: - Only shortlisted candidates will be contacted back. Dimple Jain #J-18808-Ljbffr
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