
Xcede
Xcede está com vaga(s) de emprego para Principal Machine Learning Engineer Para Lisboa em Lisboa
Cargo:
Principal Machine Learning Engineer – Lisboa
Requisitos:
PRINCIPAL MACHINE LEARNING ENGINEER
(Lisbon office x1 day a month, OR fully remote in Portugal)
Xcede are delighted to be hiring for a Principal ML Engineer on behalf of a market-leading client. In this role, you’ll be at the forefront of designing and deploying advanced, scalable, and high-performing Data & AI solutions. We’re seeking an experienced Backend Engineer with a proven track record in building robust software systems who is eager to innovate in the ever-evolving field of AI specifically.
Responsibilities
- Design for Scale:
Engineer secure, reliable, and high-performance backend systems and data infrastructures that scale seamlessly. - Pioneer Innovation:
Lead the AI division to develop and deliver cutting-edge AI models in production environments. - Set the Standard:
Showcase engineering excellence by driving best practices in coding, reviews, and the software development lifecycle. - Inspire and Guide:
Mentor senior engineers and tech leaders, helping them grow both technically and professionally. - Boost Performance:
Spearhead efforts to optimize system performance, streamline data pipelines, and enhance ETL workflows. - Integrate with Precision:
Collaborate across teams to ensure smooth incorporation of AI solutions into Kaizen’s architecture. - Stay Ahead of the Curve:
Identify and implement emerging technologies to maintain our edge in innovation. - Define the Future:
Shape the AI technical strategy to align with long-term goals, separate from immediate product priorities.
What You’ll Bring
- Over 10 years of software development experience across various languages and paradigms, with 5+ years in Python.
- Proven expertise in designing, optimizing, and scaling distributed systems and microservice architectures.
- Hands-on experience with message brokers like Kafka or RabbitMQ and advanced messaging patterns.
- Familiarity with DevOps/MLOps practices and containerization tools.
- A self-driven approach to tackling complex problems with a focus on performance, security, observability, and quality.
- A passion for monitoring and troubleshooting production systems to make data-informed decisions.
- Outstanding communication skills to bridge the gap between technical teams and diverse stakeholders.
Bonus Points
- Expertise in classic ML, deep learning, and generative AI algorithms.
- A deep understanding of the ML lifecycle and its differences from traditional software development.
- Experience building data-intensive, AI-driven products.
- Knowledge of experimentation platforms, feature serving, and model serving.
- Proficiency with big data technologies like Apache Spark, Delta Lake, Kafka, Flink, and NoSQL databases.
Salário:
a combinar
Benefícios:
Não foi informado
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