ML Engineer

Job Offer: Senior ML Engineer

Job Title: ML Engineer

Location: Marseille

Type: Full-time

Start Date: as soon as possible

About Syroco

Syroco is a Climate Tech startup that supports the energy transition of maritime transportation. It provides fleet owners and operators with a weather routing and voyage optimisation platform to improve efficiency and impact of merchant vessels. With innovation and impact being at the core of its strategy, the company was born from the complementary expertise of its founders in the scaling of hypergrowth startups, data and artificial intelligence, naval architecture, extreme sports and offshore racing.

Role Overview

We are seeking a talented and detail-oriented ML Engineer to join our team at Syroco. In this role, you will focus on designing, building, and optimizing machine learning pipelines to support the seamless training, evaluation, and integration of hybrid AI and physics-based models. Your expertise will ensure our models are scalable, efficient, and robust, capable of handling complex computational workflows with reliability.

At Syroco, our models combine machine learning algorithms with physics-informed approaches to deliver accurate and actionable insights. You’ll be responsible for scaling training workflows, optimizing computational resources, and maintaining consistent model performance across various environments

You will work closely with Data Scientists to deeply understand model architectures and with MLOps Engineers to ensure smooth deployment and monitoring of these systems. Additionally, you’ll contribute to designing and maintaining AWS SageMaker infrastructure for experimentation and large-scale training.

This role emphasizes technical expertise, a strong problem-solving mindset, and a dedication to building reliable, high-performance systems capable of supporting computationally intensive hybrid models. If you're excited about shaping the backbone of AI and physics-driven insights in a cutting-edge environment, we’d love to hear from you.

Key Responsibilities

ML Pipeline Architecture & Development:

• Design and maintain end-to-end ML pipelines on cloud platforms.
• Build scalable training environments, leveraging distributed training techniques.
• Develop efficient workflows for model experimentation and iteration, optimizing resource usage and training time. 
• Integrate hybrid models (AI + physics-informed models) seamlessly into the pipeline, ensuring compatibility and performance.

Model Optimization & Integration:

• Collaborate with Data Scientists to optimize training infrastructure and fine-tune model architectures.
• Perform profiling and benchmarking to identify and resolve resource bottlenecks.

Reliability & Monitoring:

• Set up robust monitoring and logging tools to track training, inference performance, and resource consumption.
• Identify and address anomalies, latency issues, or performance bottlenecks in ML workflows.
• Propose and implement improvements for reliability, consistency, and scalability in large-scale model training and inference pipelines.
• Ensure traceability and reproducibility of workflows across different environments.

Collaboration & Best Practices:

• Work closely with Data Scientists to ensure seamless handoff and integration of ML models.
• Enforce best practices in MLOps, focusing on infrastructure-as-code (Terraform, Terragrunt).
• Collaborate with domain experts to ensure infrastructure aligns with technical and physical constraints.

Qualifications and Experience

Educational Background: 

• Master’s degree in Computer Science, Data Science, Engineering, or a related field.

Technical Skills:

• Proficiency in Python, with strong expertise in ML frameworks (e.g., TensorFlow, PyTorch).
• Hands-on experience with AWS SageMaker or equivalent cloud-based ML platforms.
• Strong understanding of distributed training techniques and resource optimization.
• Experience with containerization technologies (e.g., Docker) for environment standardization and reproducibility.
• Familiarity with CI/CD tools and infrastructure-as-code (e.g., Terraform, Terragrunt).

Professional Experience:

• 4+ years of experience in building, deploying, and maintaining ML models in a production environment.

Soft Skills

• Strong problem-solving abilities with a pragmatic approach to technical challenges.
• Excellent communication and collaboration skills, with an ability to explain technical concepts clearly.
• Proactive, organized, and detail-oriented mindset with a focus on delivering reliable results.

What We Offer

• Competitive compensation package commensurate with experience.
• Access to company equity.
• Collaborative work environment with a commitment to sustainability and excellence.
• Professional growth and development opportunities.
• Work conditions that balance productivity and quality of life, with our office located close to the Vieux Port of Marseille.

How to Apply

If you are ready to apply your machine learning expertise to help revolutionize maritime transportation, we want to hear from you. Please submit your application, including your CV and a cover letter, to [email protected] with the subject line “ML Engineer”.