AI / Machine Learning Engineer

Key Responsibilities:

Outcome-Driven Accountability: Embrace and drive a culture of accountability for customer and business outcomes. Develop engineering solutions that solve complex problems with valuable outcomes, ensuring high-quality, lean designs and implementations.

Technical Leadership and Advocacy: Serve as the technical advocate for products, ensuring code integrity, feasibility, and alignment with business and customer goals. Lead requirement analysis, component design, development, unit testing, integrations, and support.

Engineering Craftsmanship: Maintain accountability for the integrity of code design, implementation, quality, data, and ongoing maintenance and operations. Stay hands-on, self-driven, and continuously learn new approaches, languages, and frameworks with significant focus on infusing AI/ML/GenAI where possible/appropriate. Create technical specifications, and write high-quality, supportable, scalable code ensuring all quality KPIs are met or exceeded. Demonstrate collaborative skills to work effectively with diverse teams.

Customer-Centric Engineering: Develop lean engineering solutions through rapid, inexpensive experimentation to solve customer needs. Engage with customers and product teams before, during, and after delivery to ensure the right solution is delivered at the right time.

Incremental and Iterative Delivery: Adopt a mindset that favors action and evidence over extensive planning. Utilize a learning-forward approach to navigate complexity and uncertainty, delivering lean, supportable, and maintainable solutions.

Cross-Functional Collaboration and Integration: Work collaboratively with empowered, cross-functional teams including product management, experience, and delivery. Integrate diverse perspectives to make well-informed decisions that balance feasibility, viability, usability, and value. Foster a collaborative environment that enhances team synergy and innovation.

Advanced Technical Proficiency: Possess deep expertise in modern software engineering practices and principles, including AI/ML/GenAI, Agile methodologies and DevSecOps to deliver daily product deployments using full automation from code check-in to production with all quality checks through SDLC lifecycle. Strive to be a role model, leveraging these techniques to optimize solutioning and product delivery. Demonstrate understanding of the full lifecycle product development, focusing on continuous improvement and learning.

Domain Expertise: Quickly acquire domain-specific knowledge relevant to the business or product. Translate business/user needs, architectures, and UX/UI designs into technical specifications and code. Be a valuable, flexible, and dedicated team member, supportive of teammates, and focused on quality and tech debt payoff.

Effective Communication and Influence: Exhibit exceptional communication skills, capable of articulating complex technical concepts clearly and compellingly. Inspire and influence teammates and product teams through well-structured arguments and trade-offs supported by evidence. Create coherent narratives that align technical solutions with business objectives.

Engagement and Collaborative Co-Creation: Engage and collaborate with product engineering teams at all organizational levels, including customers as needed. Build and maintain constructive relationships, fostering a culture of co-creation and shared momentum towards achieving product goals. Align diverse perspectives and drive consensus to create feasible solutions.

• A bachelor’s degree in computer science, software engineering, or a related discipline with a minimum of Second Class Upper/Upper Credit division. A Masters degree is an added advantage.
• Have a minimum of five credits in WASSCE Ordinary Level/NECO subjects or acceptable equivalent examination, including Mathematics and English Language in one sitting only.
• Strong software engineering foundation with deep understanding of OOPs, data-structure, algorithms, code instrumentations, beautiful coding practices etc.
•  Minimum of 5  years of experience with AI/ML, with last 2 years focused on GenAI as well as technologies like OpenAI, Claude, Gemini, LangChain, Agents, Vector databases, and approaches like Prompt Engineering, fine-tuning, etc.
• Proven experience in: Python, R, TensorFlow, PyTorch, Keras, Julia, ML libraries, NLP, etc.
• Proven experience with big data technologies, Angular, React, NodeJS, Python, C#, .NET Core, Java, Golang, SQL/NoSQL.
• Proven experience with cloud-native engineering, using FaaS/PaaS/micro-services on cloud hyper-scalers like Azure, AWS, and GCP.
•  Strong understanding of methodologies & tools like, XP, Lean, SAFe, DevSecOps, SRE, ADO, GitHub, SonarQube, etc.
• Excellent interpersonal and organizational skills, with the ability to handle diverse situations, complex projects, and changing priorities, behaving with passion, empathy, and care.

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Application deadline: Friday, 23 January 2025.

At Deloitte, we want everyone to feel they can be themselves and to thrive at work—in every country, in everything we do, every day. We aim to create a workplace where everyone is treated fairly and with respect, including reasonable accommodation for persons with disabilities. We seek to create and leverage our diverse workforce to build an inclusive environment across the African continent.

We actively support the inclusion of people with disabilities and embrace neurodiversity in the workplace. We recognise and value the unique strengths that neurodivergent individuals bring, and we are committed to creating an environment where everyone can thrive.

If you require reasonable accommodations in relation to your disability and neurodiverse needs during the recruitment process, please let us know. We are happy to make adjustments to suit your individual needs.

Note: The list of tasks / duties and responsibilities contained in this document is not necessarily exhaustive.  Deloitte may ask the employee to carry out additional duties or responsibilities, which may fall reasonably within the ambit of the role profile, depending on operational requirements.

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