Get a reply from this employer
Your resume and cover letter, tailored to exactly what they’re hiring for.
Living Spaces Furniture is seeking an AI/ML Learning Engineer to design, build, and deploy enterprise-grade AI solutions leveraging Microsoft and Azure stacks. You will focus on intelligent automation, predictive analytics, and COE development across business units.
The role requires 3-5+ years of hands-on experience with Azure AI tools, Python/R programming, and modern ML frameworks, enabling end-to-end model lifecycle from concept to production.
The Artificial Intelligence/Machine (AI/ML) Learning Engineer plays a vital role in designing, building, and implementing enterprise-grade Artificial Intelligence and Machine Learning solutions. This position focuses on leveraging the Microsoft and Azure stack to create and deploy intelligent automation, predictive analytics, and other AI-powered tools. This role will collaborate closely with business units to gather requirements and scope projects, and drive them to resolution, while also helping to establish and build out the company's AI Center of Excellence (COE).
Essential Duties and Responsibilities include the following. Other duties may be assigned.
Bachelor's degree (B. S.) or equivalent from four-year college in Computer Science, Data Science, Artificial Intelligence, or related field preferred. 3-5+ years of hands-on experience in data science, machine learning, or AI engineering. Demonstrable experience with the Microsoft and Azure AI stack (e.g., Azure ML, Azure Cognitive Services, Azure Databricks, Power BI). Equivalent combination of education and experience will be considered.
To perform this job successfully, an individual must have the following core capabilities. Proficiency in programming languages such as Python or R. Deep experience with the Microsoft Azure AI stack: Azure Machine Learning, Cognitive Services, Azure Databricks, Azure Data Factory. Experience with ML frameworks and libraries (e.g., Scikit-learn, TensorFlow, PyTorch). Strong understanding of data modeling, data warehousing, and predictive analytics. Knowledge of MLOps principles and tools for model deployment and management.
CCNA / CCNP preferred but not required.
This position will not have supervisory responsibilities.
The hiring pay range provides a good faith estimate of the salary or hourly wage that Living Spaces expects to pay for the position upon hire. Pay will be determined by several factors, including, but not limited to: applicant's education, relevant work experience, knowledge, applicable and relevant skills and abilities, market demand, Company budget, as well as internal equity and alignment with geographic market data. Living Spaces reserves the right to modify this page at any time.
Compensation: $105,000.00 - $140,000.00
Overtime pay is available for eligible, non-exempt Team Members. Reimbursement for expenses as required by applicable law and Company policy.Retail, Guest Services and Distribution Center Team Members are eligible to receive team bonus based on meeting specific goals and KPI's.
For more details, please visit our website at: Careers (livingspaces.com)
It is our policy to abide by all federal, state, and local laws prohibiting employment discrimination based solely on a person’s race, color, religious creed, sex, national origin, ancestry, citizenship status, pregnancy, physical disability, mental disability, age, military status, or status as a Vietnam-era or special disabled veteran, marital status, registered domestic partner or civil union status, gender (including sex stereotyping and gender identity or expression), medical condition (including but not limited to, cancer related or HIV/AIDS related), sexual orientation, or any other protected status except where a reasonable, bona fide occupational qualification exists.
Living Spaces participates in E-Verify. All newly-hired team members are queried through this electronic system established by the Department of Homeland Security (DHS) and the Social Security Administration (SSA) to verify their identity and employment eligibility.