Senior/Lead Machine Learning Engineer at IFS SOLUTIONS ASIA PACIFIC PTE LTD

Madrid, Community of Madrid, Spain -

Full Time

Start Date

Immediate

Expiry Date

13 Sep, 26

Salary

0.0

Posted On

15 Jun, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Azure, Terraform, Helm Charts, CI/CD, ArgoCD, Docker, Kubernetes, Supervised Learning, Unsupervised Learning, Deep Learning, Feature Engineering, Relational Databases, Vector Databases, TensorFlow, PyTorch

Industry

Software Development

Description

Company Description IFS is a billion-dollar revenue company with 7000+ employees on all continents. Our leading AI technology is the backbone of our award-winning enterprise software solutions, enabling our customers to be their best when it really matters–at the Moment of Service™. Our commitment to internal AI adoption has allowed us to stay at the forefront of technological advancements, ensuring our colleagues can unlock their creativity and productivity, and our solutions are always cutting-edge. At IFS, we’re flexible, we’re innovative, and we’re focused not only on how we can engage with our customers but on how we can make a real change and have a worldwide impact. We help solve some of society’s greatest challenges, fostering a better future through our agility, collaboration, and trust. We celebrate diversity and understand our responsibility to reflect the diverse world we work in. We are committed to promoting an inclusive workforce that fully represents the many different cultures, backgrounds, and viewpoints of our customers, our partners, and our communities. As a truly international company serving people from around the globe, we realize that our success is tantamount to the respect we have for those different points of view. By joining our team, you will have the opportunity to be part of a global, diverse environment; you will be joining a winning team with a commitment to sustainability; and a company where we get things done so that you can make a positive impact on the world. We’re looking for innovative and original thinkers to work in an environment where you can #MakeYourMoment so that we can help others make theirs. With the power of our AI-driven solutions, we empower our team to change the status quo and make a real difference. If you want to change the status quo, we’ll help you make your moment. Join Team Purple. Join IFS. Job Description An ML engineer at IFS is part software engineer, part dev ops engineer and ML savvy, who combines knowledge of systems and applications, machine learning and artificial intelligence to build and deploy AI-driven solutions. The work is focused on designing and maintaining high-performance, scalable AI/ML infrastructure, building, and executing ML pipelines efficiently, serving models at scale, and creating the tools for continuous monitoring and improvements. Someone in this role uses their technical know-how to translate high-value and innovative AI opportunities into deployable and sustainable products. ML engineers are well-versed on AI/ML techniques, ranging from statistical learning, computer vision to generative AI. They have strong foundations in software engineering, ML algorithms and mastered several AI/ML serving frameworks. ML engineers work in close collaboration with data scientists, data engineers, architects, and DevOps engineers, on the creation and deployment of highly scalable infrastructure and AI-driven solutions. ML engineers act as AI infrastructure experts in the development of production-ready, scalable ML pipelines and AI-driven solutions along with our data scientist, data engineers, domain experts, partners, and clients. In addition, ML engineers at IFS continuously expand their knowledge of AI infrastructure, model monitoring/observability and drift detection, functional and business process domain knowledge and share this knowledge to guide others. Qualifications Required Skills: Programming Skills: Strong proficiency in Python and experience with relevant libraries (NumPy, Pandas, Kserve, etc.). Knowledge of additional languages like Go, C#, or SQL is a plus. Cloud Platforms & Dev Ops: Familiarity with cloud computing platforms (Azure), infrastructure as code (terraform, helm charts), CI/CD, Git Ops with ArgoCD and containerization technologies (Docker, Kubernetes). AI/ML Fundamentals: Foundational understanding of machine learning concepts, including supervised and unsupervised learning, deep learning, and model evaluation techniques. Data Handling: Proficiency in data preprocessing and feature engineering. Experience with relational and vector databases. Analytical Skills: Excellent analytical skills, with the ability to interpret complex datasets and derive actionable insights. Communication Skills: Excellent verbal and written communication skills, with the ability to effectively collaborate with cross-functional teams and stakeholders Education and Experience: A bachelor's or master's degree in Computer Science, Software Engineering, Data Science, or a related field, with at least 3+ years of experience in software development, including some experience with AI/ML frameworks such as TensorFlow, PyTorch, or scikit-learn. Additional Information We embrace flexibility and hybrid work opportunities to support diverse needs and lifestyles, while also valuing inclusive workplace experiences. By fostering a sense of community, we drive innovation, strengthen connections, and nurture belonging. Our commitment ensures you can work in a way that suits you best, while also engaging with colleagues to share ideas and build meaningful relationships. In Industrial and Financial Systems Central and Eastern Europe Sp. z o.o., based in Warsaw, the Whistleblowing Procedure is in effect, outlining the methods for reporting legal violations, rules for accepting internal reports and taking follow-up actions, as well as the principles for protecting whistleblowers. Reports can be submitted through the application at https://report.whistleb.com/pl/ifs, available on the website https://www.ifs.com/.

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Responsibilities

Design and maintain high-performance, scalable AI/ML infrastructure and execute efficient ML pipelines. Translate innovative AI opportunities into sustainable, production-ready products through collaboration with cross-functional teams.