AI/ML Engineer

This is a fully remote position, open to applicants in Romania.

📋 Description

• Develop, construct, and implement machine learning models for tasks such as classification, regression, natural language processing, computer vision, and time-series forecasting.

• Choose appropriate algorithms and methodologies based on business requirements and data attributes.

• Track and enhance model performance through metrics and feedback mechanisms.

• Cleanse, preprocess, transform, and engineer features from both structured and unstructured data sources.

• Work alongside data engineers to guarantee data integrity and accessibility.

• Package and deploy models utilizing Docker, Flask/FastAPI, and Kubernetes.

• Establish CI/CD pipelines for machine learning using MLflow, Airflow, or Kubeflow.

• Oversee deployed models for drift, latency, and overall production performance.

• Convert business challenges into AI/ML use cases in collaboration with stakeholders.

• Prototype, evaluate, and scale AI-powered solutions such as recommendation systems, chatbots, and fraud detection mechanisms.

• Investigate machine learning and AI frameworks, tools, large language models, transformers, and generative AI.

• Collaborate with software developers, DevOps professionals, data analysts, and domain specialists.

• Convey technical insights into business value through thorough documentation and presentations.

• Maintain comprehensive documentation for models, experiments, and pipelines.

• Ensure reproducibility, scalability, and adherence to data governance policies.

⛳️ Requirements

• 3–5 years of practical experience in the development and deployment of machine learning models.

• Demonstrated success in addressing real-world challenges using supervised, unsupervised, or deep learning techniques.

• Proficient in Python and familiar with machine learning libraries such as scikit-learn, pandas, NumPy, TensorFlow, and PyTorch.

• Understanding of model evaluation, hyperparameter optimization, and automation of pipelines.

• Knowledge of REST APIs for model serving and integration purposes.

• Experience with MLOps tools including MLflow, Airflow, DVC, Docker, and Kubernetes.

• Familiarity with cloud machine learning services like AWS SageMaker, Azure ML, and GCP AI Platform.

• Knowledge of NLP or computer vision frameworks such as Hugging Face and OpenCV.

• Strong analytical and problem-solving skills.

• Exceptional verbal and written communication abilities.

• Capability to work autonomously as well as collaboratively within cross-functional teams.

• A strong sense of curiosity, adaptability, and a commitment to continuous learning.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Opportunities for professional development and career advancement.

• Flexible working hours and remote work options.

• Comprehensive health and wellness benefits.

• Engaging work environment with a focus on innovation and teamwork.