AI Delivery Lead
- Hybrid
- Antwerp, Vlaams Gewest, Belgium
- Delivery
Job description
By joining Faktion as a AI Delivery Lead, you join an industry leader in designing and developing enterprise-level AI solutions across various sectors. As the delivery counterpart to our team of AI experts, you have a technical background as a data scientist or machine learning expert, and have technical understanding how statistical and machine learning models transform into robust, production-grade solutions, optimizing business processes in various industries. Your responsibility extends to ensuring these models perform optimally. Your drive for innovation is key, as you explore diverse methodologies to deliver premium solutions to our clients, working closely together with our Machine Learning experts and Project Managers. The result? You help lay a solid foundation for our clients, empowering them to make strategic, data-informed decisions. In this pivotal role, you're not only advancing our technological frontiers but also enriching the knowledge base of your peers, setting new benchmarks in the AI domain. Join us to redefine the future of AI-driven business solutions.
Some key responsibilities:
- In your senior role, you assume the position of tech lead on projects, guiding your ML and Software Development colleagues through both technical and client-related aspects. You also play a pivotal role internally, propelling our company's technical prowess and enhancing our offerings to clients.
- You adeptly comprehend the business needs of customers and convert these into comprehensive technical solutions and technical designs.
- While our AI Project Managers lead the customer-facing communication, you will be intrinsic counterpart to this endeavour supporting the planning of the internal development times, and continuously translating ML and Software Engineering efforts in planning, budget and scope impacts.
- Investigate the latest in machine learning research and lead the internal assessment and integration of innovative tools and frameworks.
- Ensure the high-standard completion of projects managed by your team.
- Provide technical mentorship to junior machine learning engineers.
- Conduct workshops for clients, showcasing your knowledge and skills.
- Apply your expertise to assist the sales team in qualifying and securing exciting new projects.
Job requirements
- Excellent written and verbal communication skills in native-English or native-Dutch (French is a plus).
- Master's or PhD in Computer Science, Artificial Intelligence, or related field.
- Minimum of 5 years of experience in machine learning, with a strong focus on NLP.
- Proficiency in programming languages such as Python, Java, or Scala.
- Extensive experience with NLP libraries (e.g., NLTK, spaCy, Transformers).
- Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch).
- Excellent problem-solving and analytical skills.
- Experience with cloud computing platforms (Microsoft Azure is a plus).
Following experiences are a plus:
- Proven track record of developing and deploying scalable machine learning models.
- Publications in relevant AI/ML conferences and journals.
- Experience with in working with LLM and Foundational Models.
- Experience in mentoring and leading technical teams.
- Strong communication and teamwork abilities.
- Experience in one of our focus domains: GenAI, Data Quality, Retail, Manufacturing, Finance
We offer:
- A rewarding salary package that includes additional perks like a company car and fuel card or a mobility budget, comprehensive hospitalization and group insurance, along with a top-tier laptop and smartphone.
- Benefit from a company culture that stimulates both individual and team development, fostering your professional growth.
- Utilize your innovation budget for engaging in exciting, educational, and challenging open-source projects within your guild.
- Participate in (virtual) team-building activities and gatherings, a great opportunity to unwind and engage with our vibrant team initiatives.
- A flexible hybrid working-policy to choose where, how, and when you want to work.
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