Work setup in the employer’s posting: RemoteFrom the employer’s posting
Employment type in the employer’s posting: ContractFrom the employer’s posting
Design, build, and deploy ML models for classification, regression, NLP, vision or forecasting
Package and deploy models with Docker, Flask/FastAPI and Kubernetes
Implement CI/CD pipelines for ML using MLflow, Airflow or Kubeflow
Monitor deployed models for drift, latency and performance
Prototype AI solutions such as recommendation engines, chatbots and fraud detection
Design, build, and deploy ML models for classification, regression, NLP, computer vision, or time-series forecasting.
Package and deploy models using tools like Docker, Flask/FastAPI, and Kubernetes.
Implement CI/CD pipelines for ML using platforms like MLflow, Airflow, or Kubeflow.
Monitor deployed models for drift, latency, and performance in production environments.
Prototype and test AI-driven solutions (e.g., recommendation engines, chatbots, fraud detection).
3–5 years of hands-on experience in machine learning model development and deployment.
Python and ML libraries (scikit-learn, pandas, NumPy, TensorFlow/PyTorch)
Excellent communication skills, both verbal and written.
Ability to work independently and within cross-functional teams.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 89
Up longer than most. Similar jobs usually come down between day 6 and day 70.
Well past Uvation’s usual: its jobs come down by about day 18.
From 4,442 similar postings that came down, and 8 of Uvation’s. Coming down is not always a hire.
3 open jobs
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The AI/ML Engineer plays a critical role in designing, developing, and deploying machine learning models and AI-driven solutions to support strategic business initiatives. The role involves collaborating with cross-functional teams, including software engineering, data analytics, product development, and business stakeholders, to drive intelligent automation, data-driven decision-making, and advanced analytics capabilities. The ideal candidate will have 3 to 5 years of experience in AI/ML model development, with a strong foundation in machine learning algorithms, data preprocessing, and deployment pipelines. Experience with Python, TensorFlow/PyTorch, and cloud-based ML services is essential. Responsibilities:
Strong knowledge of: - Python and ML libraries (scikit-learn, pandas, NumPy, TensorFlow/PyTorch) - Model evaluation, hyperparameter tuning, and pipeline automation
- MLOps tools (MLflow, Airflow, DVC, Docker, Kubernetes) - Cloud ML services (AWS SageMaker, Azure ML, GCP AI Platform) - NLP or computer vision frameworks (e.g., Hugging Face, OpenCV)
3. Model Deployment and MLOps - Package and deploy models using tools like Docker, Flask/FastAPI, and Kubernetes. - Implement CI/CD pipelines for ML using platforms like MLflow, Airflow, or Kubeflow.
Familiarity with: - MLOps tools (MLflow, Airflow, DVC, Docker, Kubernetes) - Cloud ML services (AWS SageMaker, Azure ML, GCP AI Platform)
- Package and deploy models using tools like Docker, Flask/FastAPI, and Kubernetes. - Implement CI/CD pipelines for ML using platforms like MLflow, Airflow, or Kubeflow. - Monitor deployed models for drift, latency, and performance in production environments.
- Cloud ML services (AWS SageMaker, Azure ML, GCP AI Platform) - NLP or computer vision frameworks (e.g., Hugging Face, OpenCV) Soft Skills:
Complete your application on uvation.breezy.hr. The employer’s form will show what is required.
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Yes. We’ve followed 2 other AI/ML Engineer jobs there since August 2026. All 2 are still up.
New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Job Title: AI/ML Engineer
Department: IT Services
Reports To: IT Project Manager
Job Overview:
The AI/ML Engineer plays a critical role in designing, developing, and deploying machine learning models and AI-driven solutions to support strategic business initiatives. The role involves collaborating with cross-functional teams, including software engineering, data analytics, product development, and business stakeholders, to drive intelligent automation, data-driven decision-making, and advanced analytics capabilities.
The ideal candidate will have 3 to 5 years of experience in AI/ML model development, with a strong foundation in machine learning algorithms, data preprocessing, and deployment pipelines. Experience with Python, TensorFlow/PyTorch, and cloud-based ML services is essential.
Responsibilities:
1. Model Development and Optimization
2. Data Preparation and Feature Engineering
3. Model Deployment and MLOps
4. AI Solutions and Use Case Implementation
5. Research and Innovation
6. Cross-functional Collaboration
7. Documentation and Best Practices
Requirements:
Experience:
Technical Skills:
Strong knowledge of:
Familiarity with:
Soft Skills:
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India
Working pattern and location restrictions need checking in the full posting.
No clear work-authorization passage found. Eligibility is unconfirmed.