Sr. Software Engineer -AI ML/ Azure

Comp: EQUITY ONLY until revenue develops (Q124) and/or funding begins

Cloud Architecture, Azure Functions, Python, Java

Early stage beginning commercialization Q1 2024;
Chance to deploy AI / ML Open AI analytics at production scale;
Full or Part Time w/ day job ok.
Comp: EQUITY ONLY until revenue develops and/or funding begins Q32024

Team: currently 5 SwE & IT and Linguistics Data Science professionals;
Location: Dallas TX 100% remote;
Fullly remote ok Central or Eastern time zone USA;
Experience: ~8+ Years software engineering w/ 3 years machine/deep learning experience. deep expertise in Python and some Java programming and DevOps Processes.
Implementation of Python based applications on Azure cloud platform is strong preference.
Job Overview

We are seeking highly skilled and motivated NLP Developers to join our innovative early stage venture. The ideal candidate has expertise in developing and implementing NLP algorithms and models to analyze documents for semantic and syntactic ambiguity. You will be at the forefront of advancing technology to enhance document clarity, creative expression, and other quality aspects.
Required Qualifications

Education: Bachelor's or Master’s degree in Computer Science, Artificial Intelligence, Linguistics, or a related field.
Technical Expertise: Proficiency in NLP and machine learning technologies (e.g., Python, TensorFlow, PyTorch, spaCy).
Experience: Proven experience in developing NLP applications, preferably in the area of semantic and syntactic analysis.
Analytical Skills: Strong analytical and problem-solving skills, with the ability to work with complex data.
Communication: Excellent communication skills, capable of conveying complex technical ideas to non-technical stakeholders.
Design / Programming with the following :

Expertise on Azure IaaS services, including some experience with:

AKS, Azure Functions,
Azure AD,
Azure Devops,
API Management,
Kafka and Event hubs,
Change Data Capture
Cosmos DB,
Azure storage,
ADLS Gen
Knowledge on Spring, Spring Boot, Maven, Kubernetes, and other OSS technologies deemed preferable.

Hands-on other cloud technologies like GCP/AWS is an added advantage.

Key Responsibilities

Algorithm Development: Design, develop, and maintain NLP algorithms and models for analyzing semantic and syntactic structures in documents.
Data Analysis: Work with both small and large text corpuses to identify patterns, anomalies, and opportunities for improvement in document analysis.
Model Training & Optimization: Train and fine-tune machine learning models to enhance accuracy in detecting ambiguities in text.
Collaboration with Cross-Functional Teams: Collaborate with other developers and the product team to integrate NLP technologies into our platform.
Research and Innovation: Stay abreast of the latest developments inOpen AI, LLMs, machine learning, and NLP applying new techniques and methodologies to ongoing projects.
Quality Assurance: Ensure the reliability and effectiveness of NLP applications through rigorous testing and validation.
Documentation & Reporting: Document development processes and report on project progress and outcomes.