Location:Newark, NJ - hybrid onsite (LOCAL CANDIDATES ONLY!)Salary Range:Competitive salary based on experience and qualificationsIntroductionJoin our dynamic team in Newark, NJ, where you will have the opportunity to drive innovation and leverage the power of machine learning to create impactful solutions. This is a chance to work in a collaborative environment that values diversity and inclusion, and to contribute to projects that solve real-world problems and drive business growth.Required Skills & Qualifications
Applicants must be able to work directly for Artech on W2
Extensive software engineering experience with a strong working experience in machine learning
Bachelor's degree in computer science, computer engineering, or a related engineering field
Advanced proficiency with Python, Java, and Scala
Strong computer science fundamentals such as algorithms, data structures, multithreading
Experience working with Generative AI, using LangChain for Gen AI and techniques like RAG
Experience using ML and DL Libraries: XGBoost, SKlearn, Tensorflow or PyTorch
In-depth experience building solutions using public clouds such as AWS, GCP
Experience using ML platforms like SageMaker, H2O, DataRobot, etc.
Strong knowledge on ML model development life cycle components like containers, batch vs real-time inference endpoints, application security testing, etc.
Experience managing relationships in a cross-functional environment with multiple stakeholders
Experience with developing and deploying production-grade applications with ML inferences using automation pipeline on cloud
Experience working in Agile/Scrum development process
Experience in building end-to-end recommender systems
Exposure to graph databases and platforms, e.g., Neo4j
Exposure to CI/CD tools like Jenkins
Financial Services, particularly Insurance and 401K domain knowledge
AWS Solutions Architect certification
Day-to-Day Responsibilities
Lead and drive machine learning projects from inception to production
Collaborate with business leaders, subject matter experts, and decision-makers to develop success criteria and optimize new products, features, policies, and models
Partner with data scientists to understand, implement, train, and design machine learning models
Collaborate with the infrastructure team to improve the architecture, scalability, stability, and performance of ML platform
Construct optimized data pipelines to feed machine learning models
Extend existing machine learning libraries and frameworks
Develop processes, model monitoring, and governance framework for successful ML model operationalization
Define objectives for the Machine Learning platform, own the technical roadmap, and be accountable for delivering results
Define standards for engineering and operational excellence for running best-in-class ML platforms and continue to improve ML platforms to keep up with the latest innovations
Design and implement architectural best practices in the delivery of data science use cases
Company Benefits & Culture
Inclusive and diverse work environment
Opportunities for professional growth and development
Supportive team culture that encourages innovation and collaboration
For immediate consideration please click APPLY to begin the screening process with Alex.
