AI/ ML Engineer

Job Description

Summary:

We are seeking a dynamic and detail-oriented AI/ML Engineer to join our growing consulting team, where innovation meets strategic impact. In this role, you will play a pivotal part in designing, developing, and deploying machine learning models that solve complex business challenges across diverse industries. You will collaborate with cross-functional teams to translate business requirements into scalable AI solutions, leveraging cutting-edge algorithms and data-driven insights. This position offers a unique opportunity to work on high-impact client projects, contribute to thought leadership in AI adoption, and grow within a forward-thinking organization committed to technological excellence. Your work will directly influence how clients leverage artificial intelligence to optimize operations, enhance customer experiences, and drive competitive advantage.

Responsibilities:

• Design, build, and deploy machine learning models and AI solutions tailored to client-specific business problems.
  
• Conduct data exploration, preprocessing, and feature engineering to prepare high-quality datasets for model training.
  
• Develop and optimize supervised and unsupervised learning algorithms, including deep learning frameworks and NLP models.
  
• Collaborate with data scientists, consultants, and clients to define project scope, deliverables, and success metrics.
  
• Implement and maintain ML pipelines using cloud platforms (e.g., AWS, Azure, GCP) and CI/CD practices.
  
• Perform model evaluation, validation, and monitoring to ensure accuracy, scalability, and ethical compliance.
  
• Document technical workflows, model performance, and deployment processes for internal and client-facing reporting.
  
• Stay current with emerging trends in AI/ML, including generative AI, reinforcement learning, and model interpretability.
  
• Support proof-of-concept (PoC) initiatives and contribute to proposal development for new consulting engagements.
  

Requirements

Requirements:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, Engineering, or a related field.
  
• 1–3 years of hands-on experience in AI/ML development within a consulting, tech, or data-driven environment.
  
• Proficiency in Python and experience with major ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
  
• Strong understanding of statistical modeling, algorithm design, and data visualization techniques.
  
• Experience with cloud-based ML platforms (e.g., AWS SageMaker, Azure ML, Google Vertex AI).
  
• Familiarity with version control (Git), containerization (Docker), and orchestration tools (e.g., Kubernetes, Airflow).
  
• Excellent problem-solving skills and the ability to communicate technical concepts to non-technical stakeholders.
  
• Strong analytical mindset with attention to detail and a commitment to continuous learning.
  
• Willingness to travel for client engagements (as applicable).
  

Preferred Qualifications:

• Experience with natural language processing (NLP), computer vision, or time-series forecasting.
  
• Knowledge of MLOps practices and model lifecycle management.
  
• Certification in AI/ML (e.g., AWS Certified Machine Learning – Specialty, Google Professional ML Engineer).
  

Benefits

Perks and benefits

Requirements
Requirements: Bachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, Engineering, or a related field. 1–3 years of hands-on experience in AI/ML development within a consulting, tech, or data-driven environment. Proficiency in Python and experience with major ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Strong understanding of statistical modeling, algorithm design, and data visualization techniques. Experience with cloud-based ML platforms (e.g., AWS SageMaker, Azure ML, Google Vertex AI). Familiarity with version control (Git), containerization (Docker), and orchestration tools (e.g., Kubernetes, Airflow). Excellent problem-solving skills and the ability to communicate technical concepts to non-technical stakeholders. Strong analytical mindset with attention to detail and a commitment to continuous learning. Willingness to travel for client engagements (as applicable). Preferred Qualifications: Experience with natural language processing (NLP), computer vision, or time-series forecasting. Knowledge of MLOps practices and model lifecycle management. Certification in AI/ML (e.g., AWS Certified Machine Learning – Specialty, Google Professional ML Engineer).