AI​/ML Engineer

Industry: Business Consulting and Services

Are you passionate about building innovative AI and Machine Learning solutions that transform complex data into actionable insights and drive mission-critical business outcomes? We are seeking a skilled AI/ML Engineer to design, develop, and deploy intelligent applications that solve real-world challenges while collaborating closely with business stakeholders, analysts, and technical teams.

In this role, you will work across the full machine learning lifecycle—from gathering requirements and preparing data to developing, deploying, and optimizing AI-powered solutions. You will play a key role in delivering scalable analytics capabilities, maintaining data governance standards, and enabling data-driven decision-making through advanced technologies.

Key Responsibilities

• Design, develop, and deploy machine learning models and AI-driven solutions aligned with business objectives and operational requirements.
• Build and optimize machine learning tools, frameworks, and applications for a variety of analytical use cases.
• Develop predictive, classification, recommendation, and automation solutions using modern AI/ML techniques.
• Monitor, evaluate, and improve model performance to ensure accuracy, scalability, and reliability.
• Support the implementation of AI solutions across enterprise platforms and cloud environments.

Data Governance & Analytics Support

• Create and maintain data governance documentation, standards, templates, and best practices.
• Ensure data quality, integrity, security, and compliance throughout the machine learning lifecycle.
• Support data preparation, feature engineering, and model training activities using structured and unstructured datasets.
• Collaborate with data and analytics teams to establish scalable and sustainable AI workflows.

Stakeholder Engagement & Solution Delivery

• Work closely with business users and operational teams to understand requirements and translate them into technical solutions.
• Communicate complex technical concepts effectively to both technical and non-technical stakeholders.
• Participate in solution design discussions and provide recommendations on AI and machine learning opportunities.
• Support end-to-end project delivery, from requirements gathering through deployment and ongoing optimization.
• Collaborate with cross-functional teams including data engineers, software developers, business analysts, and domain experts.
• Stay current with emerging trends, tools, and technologies in artificial intelligence, machine learning, cloud computing, and advanced analytics.
• Contribute to continuous improvement initiatives and knowledge-sharing across engineering teams.
• Support the development of reusable frameworks, automation tools, and AI best practices.

Required Qualifications

• Bachelor's degree in Computer Science, Data Science, Engineering, Information Systems, Mathematics, or a related field.
• Experience designing, developing, and implementing machine learning models and AI-based applications.
• Strong understanding of machine learning algorithms, model development, validation, and deployment methodologies.
• Experience deploying and managing machine learning solutions in cloud-based environments.
• Knowledge of data engineering, analytics, and model lifecycle management principles.
• Strong programming and analytical problem-solving skills.
• Experience gathering requirements and collaborating with business stakeholders to deliver impactful solutions.
• Excellent communication and teamwork abilities.

Preferred Qualifications

• Experience with commercial AI and analytics platforms.
• Hands-on experience with cloud-native machine learning services and AI development tools.
• Knowledge of computer vision, natural language processing, predictive analytics, or deep learning frameworks.
• Experience developing custom analytics and decision-support applications.
• Familiarity with large-scale data processing, model monitoring, and MLOps practices.
• Experience working in highly regulated, security-focused, or mission-critical environments.
• Understanding of data governance, compliance, and responsible AI principles.

What Success Looks Like

• Delivering high-quality AI and machine learning solutions that generate measurable business value.
• Developing scalable and reliable analytics capabilities that support informed decision-making.
• Building strong partnerships with stakeholders and translating business challenges into technical solutions.
• Ensuring robust governance, security, and quality standards across AI initiatives.
• Driving innovation through emerging technologies and continuous improvement practices.