Description

Position Overview:

The AI/ML Engineer will be responsible for developing, implementing, and deploying advanced artificial intelligence and machine learning solutions. The ideal candidate will have strong programming skills, expertise in machine learning algorithms, and hands-on experience building scalable AI applications. This role involves working with large datasets, developing predictive models, optimizing algorithms, and integrating AI capabilities into enterprise systems.

AI/ML Technologies & Technical Expertise:

Strong programming experience with Python and machine learning frameworks.

Hands-on experience with Scikit-learn, TensorFlow, PyTorch, and Keras.

Knowledge of supervised, unsupervised, and reinforcement learning algorithms.

Experience with deep learning, neural networks, NLP, and computer vision.

Proficiency in Pandas, NumPy, SciPy, Matplotlib, and data visualization tools.

Experience with Generative AI, Large Language Models (LLMs), prompt engineering, and RAG.

Knowledge of vector databases such as Pinecone, FAISS, ChromaDB, or Weaviate.

Experience with data preprocessing, feature selection, feature engineering, and model optimization.

Familiarity with MLOps tools such as MLflow, Kubeflow, and model monitoring platforms.

Experience building and deploying REST APIs and microservices for AI/ML applications.

Understanding of cloud-based AI/ML platforms such as AWS SageMaker, Azure Machine Learning, and Google Vertex AI.

Knowledge of Docker, Kubernetes, Git, and CI/CD pipelines.

Key AI & Machine Learning Responsibilities:

Design, develop, train, test, and deploy machine learning models for business applications.

Analyze structured and unstructured datasets to identify trends and generate actionable insights.

Build predictive and classification models using appropriate machine learning algorithms.

Perform data cleaning, preprocessing, transformation, and feature engineering.

Develop deep learning, NLP, and Generative AI solutions based on business requirements.

Implement LLM-based applications using prompt engineering, RAG pipelines, and vector search.

Evaluate model accuracy, performance, scalability, and reliability.

Optimize algorithms and models to improve prediction quality and processing efficiency.

Deploy and integrate AI/ML models into production environments.

Implement model versioning, monitoring, retraining, and continuous improvement processes.

Collaborate with data engineers, software developers, data scientists, and business stakeholders.

Maintain technical documentation and follow responsible AI, security, and data privacy practices.

Experience & Professional Competencies:

6+ years of experience in Artificial Intelligence, Machine Learning, Data Science, or related engineering roles.

4+ years of hands-on experience developing machine learning models using Python.

Strong experience with machine learning algorithms, statistical modeling, and model evaluation techniques.

Practical experience deploying and maintaining production-ready AI/ML solutions.

Experience working with cloud-based machine learning environments.

Knowledge of Generative AI, LLMs, and RAG-based application development is highly desirable.

Strong analytical, mathematical, and problem-solving abilities.

Excellent communication skills and ability to work in cross-functional engineering teams.

Academic Qualifications & Preferred Certifications:

Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Mathematics, Statistics, or a related field.

Master's degree or PhD in Artificial Intelligence, Machine Learning, or Data Science is preferred.

Relevant certifications such as AWS Certified Machine Learning Engineer, Microsoft Azure AI Engineer Associate, or Google Professional Machine Learning Engineer are an advantage

Key Skills

Education

Any Graduate