MA Tech are working closely alongside a Director of Technology in core client of ours who is looking to add an experienced AI/ML Software Engineer to a newly formed team within the business.
This team is focused on developing a cutting-edge analytics platforming and deploying advanced machine learning models. You will be, from the beginning, a key member of the team delivering on strategically vital projects to the business in the fields of Artificial Intelligence and Machine Learning.
Get in touch if you are looking to add tremendous value for this business and the wider world with your expertise.
- Invent, design and build novel solutions that embody Artificial Intelligence approaches
- Develop and deploy solutions independently and as a team member
- Produce high quality solutions that are reliable and scalable
- Utilize data from disparate data sources in order to support solution features
- Liaise & communicate with key business stakeholders on the deployment and integration of AI / ML solutions
- Collaborate in a cross-functional teams
- Python, R, Java, C++, Scala or other object oriented languages
- Micro services / SOA / componentized design, development & architectural best practices
- Experience in the fundamentals, practical application, and best practices of AI/ML
- Data Quality Management & Testing experience
- Experience in Test Driven Design & implementation delivering automated tests alongside code (unit, integration, performance)
- Experience with Spark, Hadoop, MPI, or other distributed frameworks
- API Design Patterns & Implementation, SDK Development
- Experience developing & delivering applications within a CI / CD & Agile driven environment & associated best Practices
- Experience working with Dev/Model Ops
- Experiences working in HA environments, designing for resiliency
- Qualification in Machine Learning, AI, Statistics, Optimization or related discipline
- Working Knowledge of Tensorflow, PyTorch or similar other learning frameworks
- AI: Speech AI, Natural Language Understanding, Deep Learning, Classical AI (search and planning), Reinforcement Learning, Bayesian Statistics, Causal Inference