Job Title : ML Engineer
Location: REMOTE
Duration: Direct Hire

About the ML Engineer role:
You are an expert at finding patterns and explaining insights from application & event data using supervised and unsupervised ML approaches to customers. These “usage pattern cohorts” are the lynchpin of increasing the go-to-market and operational clock speed of customer-centric organizations. You will be accountable for the development, training and performance management of AIs (Engage, Economic Forecasting, & Growth). You will be analyzing diverse and dynamic data sets across application telemetry, CRM, Support, Accounting / Billing, Website Analytics and other common enterprise data sources. You will be working across 1 - 5 customers as a highly trusted (and billable) AI/ML Engineer. As joining an early stage AI-Start Up you will contribute to the expansion of  delivery methodology and AI/ML workbench.

You will:

• Aggregate, analyze and generate supervised & unsupervised ML insights from large application telemetry data sets
• Consolidate and manage high-value datasets via REST APIs or Extract, Load, Transform (ELT) processes, etc into Datalakes such as Google BigQuery, Snowflake, DataBricks, AWS S3, etc.
• Build, train, test, tune and deploy AI models at scale within a Customers’ operating architecture in platforms such as Vertex AI
• Engage with other QuadSci deployed colleagues on the explanation of data insights, confirmation of design requirements, root cause analysis, etc.
• Work with Customers on AI feature roadmaps (incl. GenAI applications) for their models and ongoing performance management of deployed AI models
• Collaborate with QuadSci colleagues and / or Customer IT on integration and automation requirements reliant on AI/ML score code outputs

Qualifications:

• Must have a bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics or other related field
• 3+ years of relevant experience in data science, consulting or product development
• Expertise in NumPy, Pandas, SciKitLearn, Keras, etc.
• Demonstrated success in the use of clustering, classification, regression, decision trees etc to deliver transformative insights
• Strong experience in building, training, and tuning predictive machine learning, especially in the domains of next best offer or recommended action based on time-series type data sets
• Experience in Natural Language Processing (NLP) for sentiment analysis and behavioral modeling
• Extensive experience in SQL, Python, Pandas data transformation to form data tables and feature stores

Advanced Qualifications - Nice to have:

• Masters degree in Computer Science, Data Science, Applied Statistics or a related field
• Experience with data science and cloud computing environments like Jupyter, VertexAI, Sagemaker, etc. Formal certifications in those are a plus.
• Hands on experience with Kedro, Dask, or Apache Spark is a major plus
• Deployment architecture experience for MLOps optimization using technologies like Kubernetes, Docker, Snowflake Container Services, etc.
• Interest and commitment to help industrialize the use of Large Language Models (LLMs) and GenerativeAI applications via API calls to OpenAI, GoogleBARD etc. and/or fine tuning Open Source LLMs
• Familiarity with technologies and/or data architectures such as: Pendo, Salesforce, HubSpot, Open Telemetry, ServiceNow, Zendesk, NetSuite, Zuora, PSA applications
• Direct experience in the use of AI/ML to automate essential business processes that have an impact to Field teams or Customers

 
 
At SPECTRAFORCE, we are committed to maintaining a workplace that ensures fair compensation and wage transparency in adherence with all applicable state and local laws. This position’s starting pay is: $ 4000.00/Monthly.