About the Role
The company is seeking an AI Developer to lead the development of intelligent solutions leveraging Artificial Intelligence technologies, focusing on Generative AI and advanced analytics. The successful candidate will transform data into valuable business insights and develop AI-powered applications that drive smarter decision-making, improve operational efficiency, and support digital transformation initiatives.
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Key Responsibilities:
- Design, develop, train, and optimize machine learning models for real applications or use cases.
- Translate business and product requirements into scalable ML/AI solutions.
- Implement feature engineering, model selection, tuning, and evaluation techniques.
- Develop and deploy ML models into production environments with high availability and performance.
- Build and maintain ML pipelines (training, validation, deployment, monitoring).
- Monitor model performance, data drift, and model decay; retrain models as needed.
- Ensure models meet reliability, scalability, and security standards.
- Work closely with Data Scientists, Product Managers, and Software Engineers.
- Collaborate with data engineering teams to ensure high-quality, reliable data pipelines.
- Participate in design and code reviews, ensuring engineering best practices.
- Optimize models for latency, throughput, and cost.
- Implement experimentation frameworks (A/B testing, offline evaluation).
- Apply responsible AI principles, including fairness, explainability, and governance where required.
Requirements & Qualifications:
- 4+ years of hands-on experience in Machine Learning or applied AI roles.
- Strong programming skills in Python (and/or Java, Scala).
- Solid understanding of ML algorithms (supervised, unsupervised, deep learning).
- Experience with frameworks such as TensorFlow, PyTorch, Scikit-learn.
- Experience deploying models using Docker, Kubernetes, or cloud ML services.
- Strong knowledge of data structures, algorithms, and software engineering principles.
- Experience working in agile, cross-functional teams.
- Experience with cloud platforms (AWS, Azure, or GCP) and managed ML services.
- Hands-on experience with MLOps tools (MLflow, Kubeflow, Airflow, SageMaker, Azure ML).
- Experience with big data technologies (Spark, Kafka, Databricks).
- Background in NLP, Computer Vision, or Generative AI.
- Strong problem-solving and analytical thinking.
- Production-first mindset.
- Data-driven decision making.
- High collaboration and communication skills.
Tools & Technologies:
- Dataiku
- SQL Server
- Power BI
- AWS Bedrock
Job Location:
Client site
