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
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