Datatonic
AI, Data Engineering, Analytics
SeniorMachineLearningEngineer
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“Senior Machine Learning Engineer at Datatonic. Skills: Machine Learning, Python, Google Cloud Platform, Data Engineering, MLOps. engineer beautiful code in Python. advocate of high-quality engineering and best-practice in production software as well as rapid prototypes”
What You'll Achieve.
future-proof their operations; unlock actionable insights; stay ahead of the curve in a rapidly evolving world; deliver innovative solutions using AI & Cloud; make an impact
Industry & Context.
solve real-world problems; ML & Data Science fundamentals; know the right tools and approach for each ML use case
What They're Looking For.
Must Have
Multiple years experience as a Machine Learning Engineer, Proficiency in Python as a backend language, Familiarity with cloud platforms such as Google Cloud, AWS, or Azure, Hands-on experience with foundational software engineering practices, Knowledge of SQL for querying and managing data, Experience scaling computations using GPUs or distributed computing systems, Familiarity with exposing machine learning components through web services or wrappers (e. g. , Flask in Python), communication and presentation skills to effectively convey technical concepts
Nice to Have
preferably with a consulting background, Scale-up experience, Cloud certifications (Google Cloud Professional Machine Learning Engineer, AWS Solution Architect, etc. )
What You'll Do.
engineer beautiful code in Python
advocate of high-quality engineering and best-practice in production software as well as rapid prototypes
lead projects and take an active role in leading client discussions
building trusted relationships with prospects
finding creative ways to use machine learning to solve problems
overseeing the delivery of these engagements
Translating Requirements: Interpret vague requirements and develop models to solve real-world problems
Data Science: Conduct ML experiments using programming languages with machine learning libraries
GenAI: Leverage generative AI to develop innovative solutions
Optimisation: Optimise machine learning solutions for performance and scalability
Custom Code: Implement tailored machine learning code to meet specific needs
Data Engineering: Ensure efficient data flow between databases and backend systems
MLOps: Automate ML workflows
and feature/metadata storage
ML Architecture Design: Create machine learning architectures using Google Cloud tools and services
Engineering Software for Production: Build and deploy production-grade software for machine learning and data-driven solutions
How You'll Work.
Communication Scope
communication and presentation skills to effectively convey technical concepts
Process & Methodology
scoping projects, overseeing the delivery of these engagements
Full Job Description
Senior Machine Learning Engineer SHAPE THE FUTURE OF AI & DATA WITH US At Datatonic, we are Google Cloud's premier partner in AI, driving transformation for world-class businesses. We push the boundaries of technology with expertise in machine learning, data engineering, and analytics on Google Cloud Platform. By partnering with us, clients future-proof their operations, unlock actionable insights, and stay ahead of the curve in a rapidly evolving world. YOUR MISSION As a Senior Machine Learning Engineer, you'll know how to engineer beautiful code in Python and take pride in what you produce. You'll be an advocate of high-quality engineering and best-practice in production software as well as rapid prototypes. Whilst the position is a hands-on technical role, we'd be particularly interested to find candidates with a desire to lead projects and take an active role in leading client discussions. Your responsibilities will involve building trusted relationships with prospects, finding creative ways to use machine learning to solve problems, scoping projects, and overseeing the delivery of these engagements. To be successful, you will need strong ML & Data Science fundamentals and will know the right tools and approach for each ML use case. You'll be comfortable with model optimisation and deployment tools and practices. Furthermore, you'll also need excellent communication and consulting skills, with the desire to meet real business needs and deliver innovative solutions using AI & Cloud. WHAT YOU’LL DO - Translating Requirements: Interpret vague requirements and develop models to solve real-world problems. - Data Science: Conduct ML experiments using programming languages with machine learning libraries. - GenAI: Leverage generative AI to develop innovative solutions. - Optimisation: Optimise machine learning solutions for performance and scalability. - Custom Code: Implement tailored machine learning code to meet specific needs. - Data Engineering: Ensure efficient
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