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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