Machine Learning Engineer
Nantes, France
Job Description
As a Senior Data Scientist / Machine Learning Engineer at Inetum's FabLab, you will play a strategic role in leading the development and implementation of ML models and data-driven solutions. Leveraging your extensive experience, you will drive client-facing engagements, participate in pre-sales activities, and provide technical leadership to junior team members.
Responsibilities:
- Lead client-facing engagements, working closely with stakeholders to understand business requirements and propose ML-based solutions.
- Drive pre-sales activities, including scoping, solution design, and presenting technical proposals to potential clients.
- Provide technical leadership and mentorship to junior team members, guiding them in the development and implementation of ML models and algorithms.
- Design, develop, and implement advanced machine learning models and algorithms for research projects, internal products, and client projects.
- Conduct exploratory data analysis, feature engineering, and model validation to ensure the robustness and accuracy of ML solutions.
- Collaborate with software engineers to integrate ML models into production systems and deploy them at scale.
- Stay abreast of the latest advancements in ML techniques and frameworks, and proactively apply them to enhance model performance and efficiency.
- Participate in research initiatives to explore emerging technologies and methodologies, and contribute to the development of innovative solutions within the FabLab.
Qualifications
- Master's degree or Ph.D in Computer Science, Engineering, Mathematics, or related field.
- 5+ years of hands-on experience in data science, machine learning, or related roles, with a strong track record of client-facing engagements or/and pre-sales activities.
- Strong proficiency in mathematical techniques such as probability, statistics, and linear algebra.
- Expertise in Python programming and experience with ML libraries/frameworks (e.g., TensorFlow, scikit-learn, PyTorch).Solid understanding of data processing techniques and frameworks (e.g., pandas, Spark).
- Experience working on research projects and industry applications, with a proven track record of delivering high-quality ML solutions.
- Excellent communication skills with the ability to effectively present technical concepts to clients and stakeholders.
- Leadership experience is preferred but not mandatory.
Preferred Qualifications:
- Experience with deep learning techniques and frameworks (e.g., CNNs, LSTMs).
- Knowledge of cloud platforms and services (e.g., Azure, AWS, Google Cloud).
- Familiarity with big data technologies and distributed computing frameworks.
- Ability to work independently and drive projects from conception to completion.
- Strong problem-solving skills and a passion for exploring innovative solutions to complex problems.
Additional Information
Benefits:
- Competitive salary and performance-based bonuses.Comprehensive health benefits package.
- Flexible work arrangements, including remote work options with regular visits to Nantes (and Paris).
- Professional development and training opportunities.Collaborative and inclusive work culture.
- Opportunity to work on cutting-edge projects at the intersection of innovation and technology within the Innovation Business Unit.
How to Apply: If you are a seasoned Data Scientist / ML Engineer with a passion for client-facing engagements, pre-sales activities, and technical leadership, we want to hear from you! Please submit your resume and a cover letter outlining your relevant experience and why you are interested in joining Inetum as a Senior Data Scientist / ML Engineer. We look forward to reviewing your application and discussing how you can contribute to our team.
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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: AWS Azure Big Data Computer Science Data analysis Deep Learning EDA Engineering Feature engineering GCP Google Cloud Linear algebra Machine Learning Mathematics ML models Pandas Python PyTorch Research Scikit-learn Spark Statistics TensorFlow
Perks/benefits: Career development Competitive pay Flex hours Health care
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