Key Responsibilities
- Lead the entire ML lifecycle from data collection and analysis to model deployment, monitoring, and optimization.
- Apply deep learning and NLP techniques to develop solutions, potentially enhancing systems like search or recommendation engines.
- Design and implement end-to-end ML pipelines, incorporating MLOps best practices for CI/CD, containerization (Docker, Kubernetes), and cloud deployment (AWS, GCP, Azure).
- Utilize LLM knowledge, including prompt engineering and fine-tuning, to build advanced generative AI applications and conversational AI solutions.
- Perform comprehensive data analytics, including statistical analysis and feature engineering, to inform model development and extract actionable insights from large datasets.
- Write production-quality, robust code in Python (and potentially other languages like Java or Scala), ensuring code quality through reviews and testing.
- Collaborate with cross-functional teams, including data scientists, data engineers, and product managers, to translate business requirements into technical ML solutions.
Requirements
Required Skills and Qualifications
- Proven experience as a Machine Learning Engineer with a strong portfolio of deployed production models.
- Proficiency in Python and relevant ML frameworks/libraries (e.g., TensorFlow, PyTorch, scikit-learn).
- Expertise in data science methodologies, statistical analysis, and data analytics.
- Hands-on experience with MLOps tools and practices for managing the ML application lifecycle.
- Strong understanding of NLP and experience with LLMs and prompt engineering techniques.
- Solid software engineering background with knowledge of data structures, algorithms, and system design.
- Excellent problem-solving, communication, and collaboration skills.
Skills Required
- Proven experience as a Machine Learning Engineer with a portfolio of deployed production models
- Proficiency in Python and machine learning frameworks or libraries such as TensorFlow, PyTorch, and scikit-learn
- Expertise in data science methodologies, statistical analysis, and data analytics
- Hands-on experience with MLOps tools and practices for managing the machine learning application lifecycle
- Strong understanding of natural language processing and experience with large language models and prompt engineering
- Solid software engineering background, including data structures, algorithms, and system design
- Strong problem-solving, communication, and collaboration skills
What We Do
A dynamic solution provider, passionate about building smart, modular, comprehensive, and sustainable solutions for today’s world of business. We resolve problems, improve operations and enhance customer experience through technology as we help our clients find better, smarter ways to perform business and modernize the way they work. Since our establishment in 2014, our 400+ Skilled engineers have been strongly committed to our 100+ enterprise Customers’ satisfaction by helping them overcome their challenges and supporting their journey towards a more agile business in more than 14 Countries. Our offices are across the globe in USA, UK, UAE, KSA and Egypt. Advansys ESC is part of INTRO Group, which was founded in 1980 and currently employs more than 2,500 skilled calibers. The group encompasses a wide range of companies in several sectors, including oil and gas, construction, pharmaceutical, engineering, and trading and commercial representation. We are specialized in a wide array of premium services including Business Automation, Low-code Development, Cloud Services, Industrial Digitization, Warehouse Automation and Strategic Outsourcing. For more info: [email protected]
