Senior Technical Consultant - Data and AI

We are seeking an experienced and skilled Senior Data & AI Engineer to join our team and assist in leading client-facing project delivery. In this role, you will be responsible for developing and deploying advanced machine learning models and AI solutions that drive business value and enable data-driven decision making for our customers. Additionally, you will play a crucial role in pre-sales activities, project scoping, and educating stakeholders on data science and machine learning concepts.

Roles and Responsibilities:

• Assist our customers in identifying, evaluating, and prioritizing AI-ready use cases.

• Design, develop, and implement complex machine learning, large language and agentic models and algorithms to solve real-world business problems.

• Collaborate with cross-functional teams, including data engineers, analysts, and subject matter experts, to understand business requirements and translate them into data science solutions.

• Lead client-facing project teams of AHEAD Data and AI experts.

• Develop and train custom ML models using frameworks such as Scikit-Learn, TensorFlow or PyTorch.

• Leverage Jupyter-based environments for exploratory data analysis, model development, and deployment.

• Communicate complex technical concepts and findings to stakeholders and leadership in a clear and concise manner.

• Mentor and provide guidance to junior AI Engineers.

• Participate in pre-sales activities, including project scoping, estimation, and solution design.

• Educate clients and stakeholders on data science and machine learning concepts, methodologies, and best practices.

• Contribute to the development and enhancement of AHEAD's Data & AI service offerings and thought leadership.

Qualifications:

• Bachelor’s or master’s degree in computer science, Statistics, Mathematics, or a related quantitative field.

• Minimum of 5 years of experience in a data science-related role, with a focus on machine learning and deep learning.

• Strong Python coding skills with an emphasis on writing efficient, scalable, and maintainable code.

• Experience with developing and training custom deep learning models using TensorFlow, PyTorch, or scikit-learn.

• Hands-on experience with Jupyter Notebooks, Azure Machine Learning Studio, Azure OpenAI, AWS SageMaker, nVidia AI Enterprise & DGX platforms

• Hands-on experience with leading open source and major model providers such as LLama, Anthropic's Claude, Open AI. Etc.

• Solid understanding of transformer architectures, attention mechanisms, and other advanced deep learning concepts.

• Knowledge of generative AI concepts, including fine-tuning, transfer learning, and RAG methods.

• Experience with the machine learning lifecycle, including model deployment, monitoring, drift detection/retraining, and canary testing.

• Strong communication and collaboration skills, with the ability to present complex technical information to both technical and non-technical audiences.

• Experience in pre-sales activities, including project scoping, estimation, and solution design.

Nice to Have:

• Bachelor’s or master’s degree in computer science, Statistics, Mathematics, or a related quantitative field.

• Minimum of 5 years of experience in a data science-related role, with a focus on machine learning and deep learning.

• Strong Python coding skills with an emphasis on writing efficient, scalable, and maintainable code.

• Experience with developing and training custom deep learning models using TensorFlow, PyTorch, or scikit-learn.

• Hands-on experience with Jupyter Notebooks, Azure Machine Learning Studio, Azure OpenAI, AWS SageMaker, Nvidia AI Enterprise & DGX platforms

• Hands-on experience with leading open source and major model providers such as LLama, Anthropic's Claude, Open AI. Etc.

• Solid understanding of transformer architectures, attention mechanisms, and other advanced deep learning concepts.

• Knowledge of generative AI concepts, including fine-tuning, transfer learning, and RAG methods.

• Experience with the machine learning lifecycle, including model deployment, monitoring, drift detection/retraining, and canary testing.

• Strong communication and collaboration skills, with the ability to present complex technical information to both technical and non-technical audiences.

• Experience in pre-sales activities, including project scoping, estimation, and solution design.