Machine Learning Engineer
DEKA Research & Development
Manchester, NH, United States
10 days ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Job source
Tech stack
Java (Programming Language)
Artificial Intelligence
Amazon Web Services
IBM DB2
Distributed Systems
Hibernate (Java)
Python (Programming Language)
Machine Learning
Microsoft SQL Server
MongoDB
NoSQL
Object-Oriented Software Development
+17 more
Oracle (Applications)
Software Engineering
Apache Zookeeper
Feature Engineering
Pytorch
Spring-mvc
Large Language Models
Apache Spark
Spring-boot
SOAPAPI
Backend
Build Management
Information Technology
Apache Kafka
Video Streaming
Data Pipelines
Microservices
Job description
We’re looking for a Machine Learning Engineer who can operate at the intersection of backend engineering and applied machine learning. If you want to design distributed systems, deploy production ML models, and architect scalable data pipelines that make a measurable difference - this is your opportunity, and it starts with the software you design and deliver at DEKA., * Design and implement scalable backend services and microservices powering data-intensive, real-world applications
- Build and deploy production ML models across the full lifecycle from feature engineering and training through evaluation, deployment, and monitoring
- Develop and maintain event-driven distributed pipelines using Apache Kafka, Apache Spark, and related technologies
- Architect systems that integrate ML models with rule-based decision engines for automated, real-time decisioning
- Collaborate across disciplines to translate complex requirements into reliable, elegant engineering solutions
- Contribute to AI/LLM-driven workflows and orchestration systems that push the boundaries of what software can do
Requirements
- M.S. in Computer Science, AI, or a related field
- 6+ years in backend software engineering and distributed systems
- Strong proficiency in Java (Spring Boot, Spring MVC, Hibernate) and Python
- Hands-on experience building and deploying production ML models (PyTorch or equivalent)
- Experience with distributed systems and streaming technologies: Apache Kafka, Apache Spark, ZooKeeper
- Solid understanding of microservices architecture, REST/SOAP APIs, and object-oriented design
- Experience with relational and NoSQL databases (Oracle, IBM Db2, MSSQL, MongoDB)
- Familiarity with AWS or equivalent cloud platforms
- Strong problem-solving skills
- Intrinsic drive to understand how things work and make them better
- Excellent communicating and collaboration across engineering, data, and product teams
- Strong attention to detail
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