Machine Learning Engineer (Remote) (Entry Level)
Jobright.ai
New york,
New york,
United States
Information Technology
H-1B
Job posted on July 15, 2025
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Job Description:
Job_Summary: Weedmaps is a leading technology company in the cannabis industry, seeking a Machine Learning Engineer to contribute to their Data organization. The role involves building and deploying sophisticated AI and machine learning systems to enhance their marketplace and e-commerce platform, collaborating with cross-functional teams to align ML initiatives with business objectives.
Responsibilities: • Develop production-ready Python-based ML models with a focus on advanced NLP, similarity metrics, and product matching and recommendations • Create and refine machine learning pipelines that can handle the unique challenges of our product data, including inconsistent naming and categorization • Develop comprehensive evaluation frameworks including evals and metrics to benchmark ML model performance in real-world scenarios • Implement automated evaluation pipelines to continuously monitor model performance in production • Build and maintain scalable ML infrastructure using a mix of managed services (eg AWS SageMaker) and custom services (such as function as a service apps on Kubernetes) • Implement best practices for model serving, versioning, and monitoring in production environments • Optimize model deployment pipelines for reliability, performance, and cost-efficiency • Design, implement, and analyze A/B (or MAB) tests to evaluate ML system performance in production systems (e.g. with Optimizely or similar tools), ensuring that ML systems achieve business objectives • Design and build API-based microservices that integrate ML functionality into our broader engineering ecosystem, ideally creating reusable ML components that can be leveraged across multiple product lines
Qualifications:
-Required: • Bachelor's degree in Computer Science, Data Science, or related quantitative field • 2+ years of experience building and deploying machine learning models in production environments • 4+ Years of relevant experience in Machine Learning, Data Science, Data/Software Engineering. • Strong programming skills in Python and experience with modern LLM endpoints • Experience with MLOps practices for model monitoring, maintenance, and lifecycle management • Demonstrated expertise in machine learning algorithms and frameworks (e.g. TensorFlow, PyTorch, or scikit-learn) as well as modern LLM systems (Anthropic, OpenAI) with a proven track record of deploying models to production • Proficiency in software engineering best practices, including version control, code review, testing, and documentation • Strong understanding of data engineering principles and experience with data preprocessing, feature engineering, and data quality assurance • History of effective collaboration with cross-functional teams to deliver ML solutions that drive measurable business results • Experience communicating complex ML concepts to both technical and non-technical stakeholders • Experience with cloud computing platforms, preferably AWS (particularly SageMaker and Bedrock)
-Preferred: • Experience using AI endpoints such as Claude or ChatGPT for embeddings and more advanced AI pipeline use cases such as hybrid ranking systems leveraging RAG with AI-based re-rankers that optimize specific metrics (e.g. precision) • Successfully built and deployed ML systems that solved real business problems in e-commerce or marketplace environments • E-commerce or marketplace business experience preferred • Regulated industry experience - nice to have
Company: Weedmaps is the world's first marijuana technology and media brand. It is a sub-organization of WM Technology. Weedmaps has a track record of offering H1B sponsorships.
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Responsibilities: • Develop production-ready Python-based ML models with a focus on advanced NLP, similarity metrics, and product matching and recommendations • Create and refine machine learning pipelines that can handle the unique challenges of our product data, including inconsistent naming and categorization • Develop comprehensive evaluation frameworks including evals and metrics to benchmark ML model performance in real-world scenarios • Implement automated evaluation pipelines to continuously monitor model performance in production • Build and maintain scalable ML infrastructure using a mix of managed services (eg AWS SageMaker) and custom services (such as function as a service apps on Kubernetes) • Implement best practices for model serving, versioning, and monitoring in production environments • Optimize model deployment pipelines for reliability, performance, and cost-efficiency • Design, implement, and analyze A/B (or MAB) tests to evaluate ML system performance in production systems (e.g. with Optimizely or similar tools), ensuring that ML systems achieve business objectives • Design and build API-based microservices that integrate ML functionality into our broader engineering ecosystem, ideally creating reusable ML components that can be leveraged across multiple product lines
Qualifications:
-Required: • Bachelor's degree in Computer Science, Data Science, or related quantitative field • 2+ years of experience building and deploying machine learning models in production environments • 4+ Years of relevant experience in Machine Learning, Data Science, Data/Software Engineering. • Strong programming skills in Python and experience with modern LLM endpoints • Experience with MLOps practices for model monitoring, maintenance, and lifecycle management • Demonstrated expertise in machine learning algorithms and frameworks (e.g. TensorFlow, PyTorch, or scikit-learn) as well as modern LLM systems (Anthropic, OpenAI) with a proven track record of deploying models to production • Proficiency in software engineering best practices, including version control, code review, testing, and documentation • Strong understanding of data engineering principles and experience with data preprocessing, feature engineering, and data quality assurance • History of effective collaboration with cross-functional teams to deliver ML solutions that drive measurable business results • Experience communicating complex ML concepts to both technical and non-technical stakeholders • Experience with cloud computing platforms, preferably AWS (particularly SageMaker and Bedrock)
-Preferred: • Experience using AI endpoints such as Claude or ChatGPT for embeddings and more advanced AI pipeline use cases such as hybrid ranking systems leveraging RAG with AI-based re-rankers that optimize specific metrics (e.g. precision) • Successfully built and deployed ML systems that solved real business problems in e-commerce or marketplace environments • E-commerce or marketplace business experience preferred • Regulated industry experience - nice to have
Company: Weedmaps is the world's first marijuana technology and media brand. It is a sub-organization of WM Technology. Weedmaps has a track record of offering H1B sponsorships.