Artificial Intelligence

Teamware Solutions is seeking a talented and innovative AI / Machine Learning Engineer to join our growing team. This pivotal role involves working with cutting-edge artificial intelligence and machine learning technologies, ensuring smooth operations, and directly contributing to our business objectives by leveraging AI to solve complex problems and drive intelligent solutions within the Artificial Intelligence (AI) domain.

Roles and Responsibilities:

• Analysis & Data Preparation:

  Conduct in-depth analysis of business problems to identify AI/ML opportunities. Perform data collection, cleansing, feature engineering, and preprocessing of large datasets to prepare them for model training.

• Model Development & Training:

  Design, develop, train, and evaluate various machine learning models (e.g., supervised, unsupervised, deep learning, NLP, computer vision) using relevant algorithms and frameworks.

• Implementation & Deployment:

  Implement AI/ML algorithms and integrate trained models into production systems and applications. Work on deployment pipelines to ensure models are scalable and performant in real-world environments.

• Troubleshooting & Optimization:

  Monitor the performance of deployed AI/ML models, troubleshoot issues, and continuously optimize models for accuracy, efficiency, and resource utilization.

• Research & Innovation:

  Stay abreast of the latest advancements, research papers, and industry trends in Artificial Intelligence and Machine Learning. Experiment with new technologies and methodologies to bring innovative solutions to the business.

• Collaboration:

  Work closely with data scientists, software engineers, product managers, and other stakeholders to understand requirements, define project scope, and deliver impactful AI-driven solutions.

• Documentation:

  Create clear and comprehensive documentation for AI models, development processes, and deployment strategies.

Preferred Candidate Profile:

Technical Proficiency:

• Strong programming skills in languages commonly used in AI/ML (e.g., Python, R, Java, Scala).
• Proficiency with key machine learning libraries and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn, Keras).
• Solid understanding of machine learning algorithms, statistical modeling, and data structures.
• Experience with data manipulation and analysis tools (e.g., Pandas, NumPy).
• Familiarity with database concepts and querying (SQL/NoSQL).

• Cloud Platforms (Plus):

  Experience with cloud-based AI/ML services and platforms (e.g., AWS SageMaker, Azure ML, Google Cloud AI Platform) is a significant advantage.

• MLOps (Plus):

  Understanding of MLOps principles, including model versioning, deployment, monitoring, and retraining strategies.

• Problem-Solving:

  Exceptional analytical and problem-solving skills with the ability to break down complex problems and devise effective AI/ML solutions.

• Communication:

  Strong verbal and written communication skills to articulate complex technical concepts to both technical and non-technical audiences.