AI/ML Developer - Lead

Job Summary:

Key Responsibilities:

Develop and Implement AI/ML Models

Design, build, and implement AI/ML models tailored to solve specific business challenges, including but not limited to natural language processing (NLP), image recognition, recommendation systems, and predictive analytics.

Model Optimisation and Evaluation

Continuously improve existing models for performance, accuracy, and scalability.

Data Preprocessing and Feature Engineering

• Collect, clean, and preprocess structured and unstructured data from various sources.
• Engineer relevant features to improve model performance and interpret ability.

Collaboration and Communication

• Collaborate closely with data scientists, back end engineers, product managers, and stakeholders to align model development with business goals.
• Communicate technical insights clearly to both technical and non-technical stakeholders.

Model Deployment and Monitoring

• Deploy models to production using MLOps practices and tools (e.g., MLflow, Docker, Kubernetes).
• Monitor live model performance, diagnose issues, and implement improvements as needed.

Staying Current with AI/ML Advancements

• Stay informed of current research, tools, and trends in AI and machine learning.
• Evaluate and recommend emerging technologies to maintain innovation within the team.

Code Reviews and Best Practices

• Participate in code reviews to ensure code quality, scalability, and adherence to best practices.
• Promote knowledge sharing and mentoring within the development team.

Required Skills and Qualifications:

• Bachelors or Masters degree in computer science, Data Science, Engineering, or a related field.

• 4-5 years' of experience in machine learning, artificial intelligence, or applied data science roles.

• Strong programming skills in Python

  (preferred) and/or R.

• Proficiency in ML libraries and frameworks

  , including: scikit-learn, XGBoost, LightGBM, TensorFlow or Keras, PyTorch

• Skilled in data preprocessing and feature engineering

  , using; pandas, numpy, sklearn.preprocessing
• Practical experience in deploying ML models into production environments using REST APIs and containers.
• Familiarity with

  version control systems

  (e.g., Git) and

  containerization tools

  (e.g., Docker).
• Experience working with cloud platforms such as

  AWS, Google Cloud Platform (GCP), or Azure

  .
• Understanding

  software development methodologies

  , especially Agile/Scrum.

• Strong analytical thinking, debugging, and problem-solving skills in real-world AI/ML applications.