AI Summary
Design, build, and deploy machine learning models into production on Google Cloud Platform. Lead development of scalable ML pipelines and implement model lifecycle management using MLflow and DVC. Collaborate with Data Engineers, DevOps, and product teams to optimize model performance and mentoring junior engineers.
Key Highlights
Production ML deployment on Google Cloud Platform
ML pipeline development and lifecycle management
Docker, Kubernetes, and CI/CD with GitLab
Key Responsibilities
Design, build, and deploy machine learning models into production on GCP
Lead development of scalable ML pipelines for data ingestion, processing, and inference
Implement model lifecycle management using MLflow and DVC
Containerize ML applications using Docker and deploy via Kubernetes
Collaborate with DevOps teams to build CI/CD pipelines using GitLab
Optimize model performance, monitoring, and reliability in production environments
Contribute to architecture decisions and best practices for ML systems
Mentor junior engineers and promote engineering excellence across teams
Technical Skills Required
Benefits & Perks
Remote position
Training and career development opportunities
Smart office
Private medical insurance
Flexible remuneration
Extra holidays
Nice to Have
Knowledge of R for data analysis
Experience working with large-scale data ecosystems (Data Engineering exposure)
Infrastructure as Code (IaC) experience
Exposure to Azure environments
Job Description
Company Description
Talan – Positive Innovation
Talan is an international consulting group specializing in innovation and business transformation through technology. With over 7,200 consultants in 21 countries and a turnover of €850M, we are committed to delivering impactful, future-ready solutions.
Talan at a Glance
Headquartered in Paris and operating globally, Talan combines technology, innovation, and empowerment to deliver measurable results for our clients. Over the past 22 years, we’ve built a strong presence in the IT and consulting landscape, and we’re on track to reach €1 billion in revenue this year.
Our Core Areas of Expertise
- Data & Technologies: We design and implement large-scale, end-to-end architecture and data solutions, including data integration, data science, visualization, Big Data, AI, and Generative AI.
- Cloud & Application Services: We integrate leading platforms such as SAP, Salesforce, Oracle, Microsoft, AWS, and IBM Maximo, helping clients transition to the cloud and improve operational efficiency.
- Management & Innovation Consulting: We lead business and digital transformation initiatives through project and change management best practices (PM, PMO, Agile, Scrum, Product Ownership), and support domains such as Supply Chain, Cybersecurity, and ESG/Low-Carbon strategies.
Job Description
You will join a global data ecosystem built on Google Cloud Platform, working on large-scale data and machine learning initiatives. The environment focuses on industrializing ML solutions—moving beyond experimentation into robust, production-ready systems. You will collaborate closely with Data Engineers, DevOps, and product teams to deploy, scale, and monitor ML models in real-world applications.
What You Will Do
- Design, build, and deploy machine learning models into production on GCP
- Lead development of scalable ML pipelines for data ingestion, processing, and inference
- Implement model lifecycle management using MLflow and DVC
- Containerize ML applications using Docker and deploy via Kubernetes
- Collaborate with DevOps teams to build CI/CD pipelines using GitLab
- Optimize model performance, monitoring, and reliability in production environments
- Contribute to architecture decisions and best practices for ML systems
- Mentor junior engineers and promote engineering excellence across teams
Interested in remote work opportunities in Machine Learning & AI? Discover Machine Learning & AI Remote Jobs featuring exclusive positions from top companies that offer flexible work arrangements.
Required:
- Strong proficiency in Python (advanced level)
- Proven experience deploying ML models into production environments
- Solid experience with Google Cloud Platform (ideally Vertex AI)
- Hands-on experience with Docker and Kubernetes
- Experience with ML lifecycle tools (MLflow, DVC)
- CI/CD experience (GitLab preferred)
- Experience working in Agile/SCRUM environments
Browse our curated collection of remote jobs across all categories and industries, featuring positions from top companies worldwide.
- Knowledge of R for data analysis
- Experience working with large-scale data ecosystems (Data Engineering exposure)
- Infrastructure as Code (IaC) experience
- Exposure to Azure environments
What do we offer you?
- Full-time contract
- Remote position based in Málaga, Spain
- Possibility to manage work permits
- Training and career development opportunities.
- Perks & Benefits: smart office, private medical inssurance, flexible remuneration, extra holidays
- Be part of a multicultural team working on international projects.
- Talan Spain’s commitment to non-discrimination based on gender, race, ideology, or any other reason, in accordance with the company’s "Equality Plan" and the current regulations on gender equality between women and men (Royal Decree-Law 6/2019).
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