Junior Quant Developer Jobs in Missouri (NOW HIRING)

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Ready to explore, break barriers, and discover more? We know you’ve got big plans – so do we! Our colleagues across the globe love innovating with science and technology to enrich people’s lives with our solutions in Healthcare, Life Science, and Electronics. Together, we dream big and are passionate about caring for our rich mix of people, customers, patients, and planet. That's why we are always looking for curious minds that see themselves imagining the unimaginable with us.

This role does not offer sponsorship for work authorization. External applicants must be eligible to work in the US.

We are looking for a Staff Applied AI Engineer to build scalable, production-grade backend applications that leverage large and complex datasets. This role is software engineering first, with a strong emphasis on designing reliable systems that ingest, process, and serve data to power modern applications and AI-driven solutions.

You will work closely with product managers, software engineers, data scientists, and ML engineers to build robust backend services, data-intensive applications, and production AI systems. Success in this role requires strong software engineering fundamentals, practical experience working with data throughout its lifecycle, and the ability to design systems that are scalable, maintainable, and reliable in production.

• Lead technical strategy for AI/LLM systems across multiple products
• Architect retrieval, orchestration, agentic, and evaluation systems that run reliably in production
• Set the standards for AI safety, evaluation, observability, and responsible rollout in aregulatedcontext
• Mentor Junior-level engineers into strong AI engineers; Employ AI Native development skills to multiply the productivity (Claude, etc.)
• Lead the frontier: evaluate new models, techniques, and tools, and bring the right ones into the team
• Design, develop, and maintain scalable Python applications and backend services.
• Build systems that ingest, validate, transform, and manage structured and unstructured data in production environments.
• Design data models and storage solutions that support scalable, high-performance applications.
• Develop reusable components for data processing, validation, enrichment, and feature generation.

• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related quantitative field.
• At least 3 years of hands-on experience in machine learning, data science, search relevance, or ranking systems.

• At least 5 years of software engineering experience, with deep recent time leading production AI/LLM systems
• Proven expertise in Python and ML frameworks (MLFlow, TensorFlow, PyTorch, Scikit- learn, or equivalent).
• Strong background in statistical analysis, data exploration, and working with large-scale datasets.
• Experience with feature engineering, data preprocessing, and data
• Seasoned hands‑on coder; still writes production Python regularly
• Seasoned system designer for AI systems at scale, retrieval, agents, evaluation, latency, and cost, vector databases/pipelines
• Strong experience building and maintaining production‑grade backend applications.
• Experience designing and developing RESTful APIs and distributed systems.
• Strong SQL skills and experience working with relational databases; familiarity with NoSQL databases or modern data storage technologies is a plus.
• Solid understanding of data engineering fundamentals, including data quality, validation, transformation, modeling, and efficient storage.
• Experience designing systems that process large datasets reliably and efficiently.
• Experience with cloud platforms such as Google Cloud Platform (GCP) or AWS.
• Experience using Docker, Git, CI/CD pipelines, automated testing frameworks, and modern software engineering best practices.

• Languages: Python, REST API, Pandas, NumPy
• Cloud and infrastructure: AWS Services and/or GCP, Kubernetes, Bedrock
• Distributed systems: event-driven architectures, including Kafka
• Orchestration Frameworks: LangGraph, LangChain, AirFlow, etc.
• Vector Databases like Qdrant

• Experience with Kubernetes and container orchestration.
• Familiarity with event-driven architectures and messaging platforms such as Kafka.
• Familiarity with ML model deployment and inference pipelines.

This role can be based in either our St. Louis, MO or Burlington, MA office and requires a weekly onsite presence.

Pay Range for this position: $110,500 - $185,900. The offer range represents the anticipated low and high end of the base pay compensation for this position. The actual compensation offered will be determined by factors such as location, level of experience, education, skills, and other job-related factors. Position may be eligible for sales or performance-based bonuses.

• Health insurance
• Paid time off (PTO)
• Retirement contributions
• Other perquisites
• Sales or performance-based bonuses (if eligible)

We are curious minds that come from a broad range of backgrounds, perspectives, and life experiences. We believe that this variety drives excellence and innovation, strengthening our ability to lead in science and technology. We are committed to creating access and opportunities for all to develop and grow at your own pace. Join us in building a culture of inclusion and belonging that impacts millions and empowers everyone to work their magic and champion human progress!