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 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 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
Applicant Notices & Disclaimers
For information on benefits, equal opportunity employment, and location-specific applicant notices, click here
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.
