DESCRIPTION
Are you a MLOps Engineer looking for a new great challenge? If you are looking for a great team with a high technical level, where proactivity and the desire to do different things are valued.
THIS IS YOUR PLACE!
We are leaders in digital solutions with 25 locations on 5 continents and a team of more than 4,500 people. We support large companies and public administrations in their end2end digital transformation process, developing and executing the most innovative and scalable projects from strategy to operation.
All this growth is based on talent and passion for innovation and continuous improvement, always in our way: simplifying the complex
JOB DESCRIPTION:
MLOps Engineer – EA, Machine Learning Operations & Cloud Platforms
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Experience with Cloud Platforms such as Azure
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Programming Languages and Frameworks: Python, Java, C#, .NET
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Prior work with TensorFlow, PyTorch, Scikit-learn, SciPy, NumPy, Pandas, Hugging Face Transformers, LangChain, OpenAI, Javascript, HTML, and CSS.
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Data Storage and Processing: Apache Spark, Data Lakes, Data Warehouses, SQL, NoSQL
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Scripting: Powershell & Bash
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Experience with CI/CD tools e.g. Azure DevOps
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Containerization: Docker, Kubernetes, Helm, and Istio.
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Version Control: Proficiency with Git.
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Monitoring/Logging: Prometheus, Grafana, and Azure Monito
REQUIREMENTS
Detailed Description:
Responsibilities will include, but not be limited to:
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Collaborate with stakeholders: Engage with business stakeholders, data scientists, software engineers, and other teams to understand their requirements and align machine learning initiatives with overall business goals.
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Integration and interoperability: Work on solutions that seamlessly integrate with existing enterprise systems, databases, and APIs. Collaborate with internal and external partners to enable smooth data flow and interoperability across systems, ensuring consistent and accurate inputs for machine learning models.
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Model deployment and monitoring: Define and implement robust processes for deploying machine learning models into production environments. Establish monitoring mechanisms to track model performance, identify anomalies, and trigger retraining or updates when necessary. Ensure models comply with regulatory and compliance standards.
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Risk assessment and mitigation: Identify potential risks and challenges related to machine learning operations, such as data privacy, security vulnerabilities, or ethical considerations. Propose and implement mitigation strategies to ensure compliance, data integrity, and model robustness.
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Continuous improvement: Continuously evaluate and optimize the machine learning operations infrastructure and processes to improve efficiency, reliability, and scalability. Stay informed about advancements in machine learning operations and recommend new tools, frameworks, or methodologies that can enhance the organization's capabilities.
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Data operations: Build and support data flows for moving or sourcing data sets for training. This includes understanding the data requirements, identifying the best methods for data transfer, and implementing the data pipelines.
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Deploy machine learning models into production environments using Azure Machine Learning Studio, Azure Kubernetes, and Kubernetes on prem.
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Design inference pipeline and set up infrastructure including data storage and data movement, compute instances, and networking.
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Create and manage Azure DevOps (ADO) pipelines to automate the end-to-end machine learning lifecycle.
Implement monitoring and logging solutions to track model performance and detect anomalies with the model, inference pipelines, data movement pipelines, and infrastructure.
Requirements:
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Proficient in Python, and knowledge of C#, and Java, with background knowledge of scripting languages and tools.
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Strong knowledge of machine learning concepts, frameworks and technologies, such as TensorFlow, PyTorch, Scikit-learn, SciPy, NumPy, Pandas, Hugging Face, and OpenAI
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Experience with MLOps tools and practices, such as CI/CD, Docker, Kubernetes, and MLflow
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Experience with SQL and NoSQL database e.g. MSSQL and PostgreSQL
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Proficiency in designing and deploying machine learning models in cloud environments (e.g., Azure/Azure ML, AWS, GCP, AKS, and K8s)
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Experience with building Docker images and managing different environments with centralized container registries.
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Proficient with using K8s for deploying models, inference workloads, and applications.
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Demonstrated expertise in architecting scalable and secure machine learning infrastructure, including data pipelines, storage systems, and model deployment frameworks
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Excellent communication and collaboration skills, with the ability to effectively engage with stakeholders at various levels of the organization
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Ability to multitask and manage multiple activities simultaneously
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Ability to use a wide degree of creativity and latitude to think differently, challenge conventional wisdom, and drive new best practices
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Ability to work effectively with international teams
Do we share the same DNA? We do, if:
- You are flexible and purpose-oriented
- You have a creative and innovative mind
- You feel confident and enjoy what you do
You are autonomous and have a self-driven personality
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Benefits of working together:
️ Law benefits
Medical insurance
Work in national & international projects
English classes
Gym pass with exclusive prices
Referral bonus
International Mobility
L Language classes, technical certifications, and Access to open webinars and Udemy
Great work environment; our teams make it possible!
Work from home and flexible hours
Various health and wellness initiatives with our VASS Care program
Stability and future projection through the professional development plan
You will be part of a dynamic company that is constantly growing
You will participate in projects with cutting-edge technologies
You will be part of a young, multifunctional, and autonomous team
You will be part of a large team of high-level professionals whose motivation is contributing value to daily work and professional excellence
If you want to join a dynamic company where technological challenges will be found daily, we await you in the great VASS team.
We want you to be the best version of yourself. YOUR TALENT IS OUR DNA
Welcome to your future!
VASS is proud to be an Equal Opportunity Employer. We do not discriminate based on race, religion, color, sex, gender identity, sexual orientation, age, national origin, marital status, or disability. Our recruitment is decided based on qualifications, merit, and business need.
