AI/ML Engineers

AI/ML Engineers

Romania

The Role:

Job Title: AI/ML Engineer

Department: IT Services

Reports To: IT Project Manager 

Location: Remote

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
- functional teams, including software engineering, data analytics, product development, and business stakeholders, to drive intelligent automation,
- driven
- making, and advanced analytics capabilities.

The ideal candidate will have 2 to 7 years of experience in AI/ML model development, with a strong foundation in machine learning algorithms, data preprocessing, and deployment pipelines. Experience with Python, Tensor
Flow/Py
Torch, and
- based ML services is essential.

Responsibilities:

1. Model Development and Optimization

• Design, build, and deploy ML models for classification, regression, NLP, computer vision, or
  - series forecasting.
• Select appropriate algorithms and techniques based on business needs and data characteristics.
• Continuously monitor and improve model performance using metrics and feedback loops.

2. Data Preparation and Feature Engineering

• Clean, preprocess, and transform structured and unstructured datasets for training and inference.
• Engineer and select relevant features to improve model accuracy and generalizability.
• Collaborate with data engineers to ensure data quality and accessibility.

3. Model Deployment and MLOps

• Package and deploy models using tools like Docker, Flask/Fast
  API, 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.

4. AI Solutions and Use Case Implementation

• Work with business stakeholders to translate
  - world problems into AI/ML use cases.
• Prototype and test AI-driven solutions (e. g. , recommendation engines, chatbots, fraud detection).
• Contribute to
  -
  - concept projects and assist in scaling successful models to production.

5. Research and Innovation

• Stay updated with the latest research, frameworks, and tools in machine learning and AI.
• Experiment with
  - edge models (e. g. , LLMs, transformers, generative AI) and assess their viability.
• Promote innovation by recommending and implementing modern AI strategies.

6. Cross-functional Collaboration

• Collaborate with software developers, Dev
  Ops, data analysts, and domain experts for
  -
  - end solution delivery.
• Translate technical insights into business value through clear documentation and presentations.

7. Documentation and Best Practices

• Maintain comprehensive documentation for models, experiments, and pipelines.
• Ensure reproducibility, scalability, and compliance with data governance policies.

Ideal Profile:

Requirements:

Experience:

• 2–7 years of
  - on experience in machine learning model development and deployment.
• Proven track record of solving
  - world problems using supervised, unsupervised, or deep learning methods.

Technical Skills:

Strong knowledge of:

• Python and ML libraries (scikit-learn, pandas, Num
  Py, Tensor
  Flow/Py
  Torch)
• Model evaluation, hyperparameter tuning, and pipeline automation
• REST APIs for model serving and integration

Familiarity with:

• MLOps tools (MLflow, Airflow, DVC, Docker, Kubernetes)
• Cloud ML services (AWS Sage
  Maker, Azure ML, GCP AI Platform)
• NLP or computer vision frameworks (e. g. , Hugging Face, Open
  CV)

Soft Skills:

• Strong analytical and
  - solving abilities.
• Excellent communication skills, both verbal and written.
• Ability to work independently and within
  - functional teams.
• Curiosity, adaptability, and willingness to learn continuously.

What's on Offer?

• Great work environment
• Excellent career development opportunities
• Attractive salary & benefits