Machine Learning Engineer

About AxiumAI - Join a Thrilling Journey in AI and Innovation At AxiumAI, we are revolutionizing the way AI and Machine Learning transform industries. As a tech-driven AI startup, we are at the forefront of cutting-edge technology, leveraging Machine Learning, Generative AI, and real-time data analysis to create impactful solutions. If you’re passionate about innovation and thrive on ambitious goals, you’ll feel right at home here. Why Join Us? At AxiumAI, we believe that small teams achieve big things. Our philosophy is simple: empowered individuals create extraordinary outcomes. We are assembling a world-class AI and Engineering team where every contributor has the opportunity to leave a profound impact. Here, your ideas won’t just be heard—they’ll be implemented. Our culture is fast-paced and dynamic. We encourage bold thinking and thrive on innovation. The best ideas win, and we aren’t afraid to push boundaries to drive meaningful change. If you want to work on exciting, high-impact challenges that push the limits of technology, AxiumAI is where you belong. Our Values · Innovation with Purpose: We're transforming an industry through cutting-edge technology that makes a real impact. · Continuous Learning: In the fast-evolving world of AI, we stay curious and support each other's growth, celebrating both breakthroughs and learning opportunities. · Trust and Excellence: We build reliable systems because we're reliable people. We take ownership of our work and deliver excellence through collaboration. · Inclusive Innovation: We are a multicultural business that thrives on diverse perspectives. Whatever your background, you'll have a voice here and the space to do your best work. We believe different viewpoints lead to better solutions and more innovative products. Join AxiumAI and become part of a team where you can shape the future of AI while growing alongside some of the most talented minds in the industry. Together, we’re redefining what’s possible. Let’s create something extraordinary. Purpose of the Role We're actively building a next-generation platform that creates personalized customer experiences at unprecedented scale. Our systems process billions of real-time data points daily, combining advanced ML models and large language models to deliver context-aware experiences worldwide. Through rapid model optimization and continuous experimentation, we drive engagement through intelligent recommendations and personalized content, delivering over 10%+ revenue growth for our clients & partners. As a member of the AxiumAI team, you will have all the tools of modern NLP and NLG at your disposal, from best-in-class LLMs, multimodal foundation models, and hybrid vector databases to all the infrastructure needed to fine-tune, evaluate, and serve your own models in production. You will also go beyond model training to achieve state-of-the-art AI performance in production, in every meaning of the word “performance”: not just accuracy and quality of outputs, but also latency, reliability, and capability of the end-to-end user-facing system as a whole. Successful machine learning engineers on the team are just as motivated to design and evolve great compound AI systems and their components as they are to train great models. Join us in building the future of intelligent systems that operate at scale with unwavering reliability. Key Responsibilities As a Machine Learning Engineer at AxiumAI, you'll be instrumental in shaping our technical foundation and ML infrastructure. You'll work directly with the founding team to build and scale our AI-driven platform from the ground up. How you will make 10X Impact:

• Own the end-to-end ML infrastructure, from initial architecture decisions to production deployment, setting the technical standards for our growing team.
• Take the lead in bridging research and production, turning innovative ML concepts into scalable, production-ready systems that process billions of real-time data points.
• Design and implement robust ML pipelines that can handle our rapidly growing data volume while maintaining exceptional performance.
• Build and optimize core model components with a focus on real-world impact, directly contributing to our mission of transforming gaming experiences.
• Drives incremental improvements (across quality, ease of (re)use, performance) within the data, from PoC to production-grade systems that can scale reliably.
• Establish best practices for code quality, testing, and documentation that will shape our engineering culture .
• Create and maintain scalable data pipelines and APIs that can handle increasing complexity while maintaining reliability.
• Works as part of a multi-disciplinary team, composed of data scientists, front-end and back-end engineers, product managers, and analysts.

• Strong track record of building and deploying ML systems in production, with hands-on experience in real-time, high-throughput environments.
• Strong foundation in applied ML frameworks and data science tools and libraries.
• Deep expertise in Python, with a focus on ML engineering best practices and production-grade code architecture.
• Experience with modern cloud platforms (AWS/GCP/Azure) and MLOps practices, including containerization and CI/CD for ML workflows.
• Practical exposure to modern cloud data platforms, with direct experience delivering data centric solutions for mission critical use cases; as well as driving innovation PoV style delivery and associated engineering/design principles.
• Experience in distributed microservice architecture and REST API development. Hands-on experience with streaming architectures and real-time processing systems.
• Track record of making architectural decisions that balance innovation with reliability.
• Demonstrated ability to work independently and drive technical initiatives from concept to production.
• Evidence of motivation to learn, and curiosity around modern approaches to ML engineering. Ability to discuss and debate relative merits and opportunities.

• Experience with LLMs and modern NLP techniques. Building and optimizing RAG systems, working with embedding models and vector stores.
• Background in scaling ML systems from prototype to production.
• Previous experience in a fast paced startup environment.
• Understanding of ML monitoring and observability best practices.

• Honesty and integrity
• Team spirit
• Motivated, curious, and eager to learn
• Passionate
• Fast and keen learner
• Self-awareness
• Sense of responsibility