Lead enterprise AI and machine learning strategy, architecture, development, and production deployment. Design predictive analytics, generative AI, LLM, RAG, and agent solutions; establish MLOps, governance, monitoring, and responsible AI practices; align initiatives with business value and ROI; communicate with executives and stakeholders; prioritize and deliver AI programs; and mentor data scientists, ML engineers, and analysts.
About Aligned Automation
At Aligned Automation, we live by our "Better Together" philosophy to build a better world. As a strategic service provider to Fortune 500 companies, we help digitize enterprise operations and drive impactful business strategies. Our purpose goes beyond projects—we strive to deliver meaningful, sustainable change that shapes a more optimistic and equitable future.
Our culture is deeply rooted in our 4Cs—Care, Courage, Curiosity, and Collaboration—ensuring that each employee is empowered to grow, innovate, and thrive in an inclusive workplace.
Role Overview
We are looking for an experienced AI/ML Lead with 8-12 years of experience in designing, developing, and deploying advanced Artificial Intelligence and Machine Learning solutions. The ideal candidate will have strong expertise in predictive analytics, Generative AI, MLOps, cloud-based AI architectures, and stakeholder management. This role requires a blend of technical leadership, business acumen, and team mentoring capabilities to drive AI initiatives that deliver measurable business impact.
AI & Machine Learning Strategy
- Design and implement machine learning, predictive analytics, and Generative AI solutions to solve complex business problems.
- Lead the development of scalable AI/ML models from ideation to production deployment.
- Evaluate and adopt emerging AI technologies, frameworks, and best practices.
- Define AI/ML architecture and deployment strategies across cloud environments.
- Establish MLOps best practices for model development, testing, deployment, monitoring, and governance.
- Ensure scalability, reliability, and performance optimization of AI systems in production.
- Collaborate with business stakeholders to identify high-impact AI use cases.
- Translate business objectives into AI-driven solutions with measurable ROI.
- Prioritize AI initiatives based on business value, feasibility, and strategic importance.
- Ensure compliance with data privacy regulations and security standards.
- Implement responsible AI practices to address fairness, transparency, and algorithmic bias.
- Establish governance frameworks for AI model lifecycle management.
- Communicate complex AI concepts and technical recommendations to executive and non-technical audiences.
- Partner with business leaders, product teams, and engineering teams to drive successful AI adoption.
- Provide regular updates on AI initiatives, risks, and business outcomes.
- Mentor and guide Data Scientists, ML Engineers, and Data Analysts.
- Foster innovation, collaboration, and continuous learning within the AI team.
- Support hiring, capability building, and technical growth of team members.
- Evaluate and prioritize AI/ML projects based on strategic alignment and expected business impact.
- Drive end-to-end execution while ensuring timely delivery and quality outcomes.
- Identify and eliminate low-value initiatives early to maximize resource utilization.
Technical Skills
- 8-12 years of experience in Data Science, Machine Learning, AI, or related domains.
- Strong expertise in Machine Learning, Deep Learning, Predictive Modeling, and Generative AI.
- Hands-on experience with Python and AI/ML frameworks such as TensorFlow, PyTorch, Scikit-learn, LangChain, and Hugging Face.
- Experience with LLMs, RAG architectures, AI Agents, and prompt engineering.
- Strong understanding of MLOps tools and practices.
- Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
- Knowledge of model monitoring, CI/CD pipelines, containerization, and orchestration tools (Docker, Kubernetes).
- Strong stakeholder management and executive communication skills.
- Proven ability to align AI initiatives with business goals and ROI objectives.
- Experience leading cross-functional teams and managing multiple AI programs simultaneously.
- Ability to mentor and develop high-performing AI teams.
- Experience in enterprise-scale AI transformation programs.
- Exposure to Responsible AI and AI Governance frameworks.
- Relevant certifications in AI/ML, Cloud, or Data Science.
- Master's degree or Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or related field.
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