Machine Learning Engineer
1 week ago
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 define ML solutions and develop Proof of Concepts (POCs). Design, build, and deploy production‑grade machine learning models using MLOps best practices (versioning, CI/CD, monitoring, retraining). Build and maintain scalable data pipelines to support model performance and system efficiency. Ensure all models adhere to organizational AI governance, compliance, and ethical AI practices . Support data exploration , feature engineering , and model optimization as needed. Automate processes for model retraining, validation, and monitoring to maintain performance over time. Document ML workflows, governance checkpoints, and model risk assessments. Collaborate with DevOps, IT, and security teams to integrate ML systems into enterprise infrastructure. Communicate technical solutions and results clearly to both technical and non‑technical audiences. Work independently while maintaining strong alignment with key project stakeholders. Job Requirements Mandatory Master's degree in Artificial Intelligence, Machine Learning, Data Science , or a related field. Minimum 6+ years of experience in data science and machine learning, including at least 3+ years in ML engineering roles. Proven experience in end-to-end ML lifecycle - from data preparation and model development to deployment and monitoring. Strong programming skills in Python (pandas, scikit‑learn, TensorFlow, PyTorch, etc.). Hands‑on experience with MLOps tools (MLflow, Airflow, TFX, Kubeflow, etc.). Familiarity with cloud platforms (AWS, GCP, Azure) for ML deployment. Strong understanding of NoSQL databases ; exposure to graph databases is advantageous. Experience with CI/CD pipelines and containerization tools (Docker, Kubernetes). Solid understanding of AI governance , model risk management , and compliance principles. Excellent communication skills with the ability to explain technical concepts to diverse audiences. Preferred Experience implementing Responsible AI frameworks and performing bias/fairness assessments . Familiarity with feature stores , model registries , and data versioning . Understanding of data privacy , anonymization , and compliance best practices. Professional Skills and Mindset Strong analytical and problem‑solving abilities. Excellent organizational and interpersonal communication skills. Eagerness to learn and adopt emerging technologies. Familiarity with software development life cycle and Agile methodologies. Collaborative mindset with respect for cultural diversity and global teamwork. Next Step If interested, you can click on "Apply here" or with your updated resume. NOTE: Only shortlisted candidates will be contacted back. Dimple JainDirect Line: 8110 4***EA License No: 91C2918Personnel Registration Number: R #J-18808-Ljbffr
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Machine Learning Engineer
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Machine Learning Engineer
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Machine Learning Engineer
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