Overview
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 write an e-mail to ***********@adecco.com with your updated resume.
Note:
Only shortlisted candidates will be contacted back.
Dimple Jain
Direct Line: 8110 4***
EA License No: 91C2918
Personnel Registration Number: R
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