AI​/ML Engineers

Join to apply for the AI/ML Engineers role at Uvation

$14,400.00/yr - $19,200.00/yr

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.

• Model Development and Optimization:
  Design, build, and deploy ML models for classification, regression, NLP, computer vision, or time‑series forecasting.
• Algorithm Selection and Continuous Improvement:
  Select appropriate algorithms and techniques based on business needs and data characteristics; continuously monitor and improve model performance using metrics and feedback loops.
• Data Preparation and Feature Engineering:
  Clean, preprocess, and transform structured and unstructured datasets; engineer and select relevant features to improve model accuracy and generalizability.
• Collaboration with Data Engineers:
  Ensure data quality and accessibility.
• Model Deployment and MLOps:
  Package and deploy models using Docker, Flask/FastAPI, Kubernetes; implement CI/CD pipelines with MLflow, Airflow, or Kubeflow; monitor deployed models for drift, latency, and performance.
• AI Solutions and Use Case Implementation:
  Translate real‑world problems into AI/ML use cases; prototype and test AI‑driven solutions such as recommendation engines, chatbots, fraud detection; contribute to proof‑of‑concept projects.
• Research and Innovation:
  Stay updated with latest research; experiment with cutting‑edge models (LLMs, transformers, generative AI); recommend modern AI strategies.
• Cross‑functional
  
  Collaboration:
  
  Partner with software developers, Dev Ops, data analysts, domain experts; document and present technical insights.
• Documentation and Best Practices:
  Maintain comprehensive documentation; ensure reproducibility, scalability, and compliance with data governance.

• 2–7 years of experience in machine learning model development and deployment.
• Proven track record solving real‑world problems using supervised, unsupervised, or deep learning methods.
• Strong knowledge of Python and ML libraries (scikit‑learn, pandas, Num Py, Tensor Flow/PyTorch).
• Experience with MLOps tools (MLflow, Airflow, DVC, Docker, Kubernetes) and cloud ML services (AWS Sage Maker, Azure ML, GCP AI Platform).
• Familiarity with NLP or computer vision frameworks (Hugging Face, OpenCV).
• Excellent communication skills, ability to work independently and within cross‑functional teams.
• Curiosity, adaptability, and willingness to learn continuously.

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