Senior Deep Learning Engineer Intern - STS21 (February 2025 Start)

• This is an unpaid internship at this time and is suitable for new recent Master's graduate candidates that wants to be a Senior Deep Learning Engineers.***
  
  

Company Overview

Flow Global Software Technologies, LLC., operating in the Information Technology (IT) sector, is a cutting-edge high-tech enterprise AI company that engages in the design, engineering, marketing, sales, and 5-star support of a cloud-based enterprise AI platform with patent pending artificial intelligence, deep learning, and other core proprietary technologies awaiting patent approval. Flow Turbo™, the company's first product, is a brand of next-generation SaaS AI sales prospecting platform that is designed to maximize the productivity day-to-day for B2B sales representatives within B2B outbound, inbound, and inside sales organizations of B2B companies. The company also provides world-class award-winning customer support, professional services, guidance, certifications, training, and advisory services. The company is headquartered in Austin, Texas and is registered in Delaware.

Position Overview

Flow is seeking highly experienced and highly dedicated Senior Deep Learning Engineer Interns to join our world-class engineering organization. This position is a premier opportunity for candidates to engage deeply in the technically rigorous world of data science and data engineering, focusing on Java and Python development, data extraction, data mining, and advanced AI model training, all while leveraging state-of-the-art cloud infrastructure. As a Senior Data Scientist Intern, you will engage in technically complex data extraction tasks, leveraging Java and Python development, and advanced tools such as Puppeteer, and Selenium for high-volume data extraction and data mining. In this role, you will be immersed in a high-pressure, technically rigorous environment where you will tackle complex data science challenges and contribute directly to our cutting-edge AI projects, produce results in sophisticated data extraction, data collection, and data mining techniques that are pivotal for all sales professionals, and Flow's AI platforms.

The ideal candidate for this position is required to demonstrate unparalleled expertise in advanced technical domains, particularly in the intricate interplay of Python and Java programming, with capabilities that surpass standard expectations by orders of magnitude. This role demands mastery in the design, implementation, and optimization of data parsing mechanisms employing regular expressions (regex) for complex pattern matching and extraction across multifaceted data streams. Expertise in natural language processing (NLP) methodologies is paramount, including deep experience in Named Entity Recognition (NER) pipelines, both standard and custom-engineered, utilizing state-of-the-art frameworks such as SpaCy, enhanced by hierarchical entity extraction techniques and contextual embeddings derived from transformer-based models like BERT or RoBERTa.

Transformer-based NLP expertise is crucial for this role, with implementations ranging from multi-modal NER pipelines to contextually aware hierarchical entity resolution. The ability to fine-tune transformer models on domain-specific data and deploy these systems into low-latency production environments is a key requirement. Candidates must integrate contextual clustering mechanisms to identify and group semantically similar entities with precision, creating actionable intelligence pipelines that redefine industry standards.

Candidates must exhibit substantial acumen in associative data methodologies and be adept in web scraping, leveraging libraries such as BeautifulSoup for DOM parsing and XPath-based heuristics to extract structured and unstructured data from HTML. Expertise in deploying headless browser technologies like Selenium, Puppeteer, and Playwright is crucial for dynamically rendering and extracting data from complex web pages. Additionally, candidates should be an expert in constructing probabilistic graph representations and interfacing with graph databases such as Neo4j and JanusGraph, ensuring efficient and scalable storage and retrieval of knowledge graph structures.

The role also emphasizes the application of Graph Neural Networks (GNNs) for advanced entity disambiguation tasks, enabling the resolution of ambiguities in large-scale data ecosystems. Extreme technical competency in Contextual Clustering algorithms, employing fuzzy matching techniques and similarity measures like Levenshtein distance, is essential for deduplication and association in high-dimensional data spaces. Expertise in Approximate Nearest Neighbor (ANN) algorithms and transformer-derived embeddings, such as Sentence-BERT, is required for high-performance similarity computations and clustering.

This position further necessitates a deep understanding of constructing and querying distributed knowledge graphs, employing ANN techniques to optimize search and retrieval operations. A profound command of advanced algorithms like Luhn's algorithm for textual summarization and other computational heuristics is required. The candidate must also exhibit exceptional capability in creating and maintaining open-source NER models, implementing custom pipelines tailored for domain-specific entity extraction and information retrieval.

Candidates must work remotely and dedicate a minimum of 30 hours per week, maintaining consistent availability and adhering to rigorous performance standards, and commit to staying at the company for at least 6 months. A completed Master's degree in Computer Science, Data Science, or Distributed Systems is a strict prerequisite, combined with a proven track record of delivering innovative solutions in technically rigorous environments. The emphasis is on unequivocal expertise in Java and Python, with all facets of the role demanding advanced-level proficiency in both languages to architect, develop, and optimize complex distributed systems, big data engineering, deep learning, and AI at scale. This role is tailored for those whose technical expertise and problem-solving acumen align with the highest echelons of engineering excellence.

• MUST BE ABLE TO COMMIT STAYING AT THE COMPANY FOR AT LEAST A BARE MINIMUM OF 6 MONTHS.***
  
  

Key Responsibilities

• Advanced Expert-Level Data Parsing & Extraction
• Apply advanced expert-level knowledge of regex to handle intricate data parsing tasks with precision.
• Develop and implement complex data extraction processes using BeautifulSoup, DOM-based XPath heuristics, and other advanced tools.
• Utilize headless browsers such as Selenium, Puppeteer, and Playwright for scalable and efficient web scraping.
• Advanced Expert-Level NLP & Named Entity Recognition
• Design and implement custom NER pipelines using SpaCy or similar open-source tools, with advanced customization and optimization.
• Lead the development of Hierarchical Entity Extraction for unstructured datasets at scale.
• Fine-tune and deploy transformer-based models like BERT and RoBERTa on specialized labeled datasets.
• Advance contextual embeddings using models such as Sentence-BERT for high-accuracy NLP deployments.
• Graph-Based Associativity & Knowledge Representation
• Construct and optimize probabilistic graphs and distributed knowledge graphs using tools like Neo4j or JanusGraph.
• Implement Graph Neural Networks (GNNs) for entity disambiguation and advanced relationship modeling.
• Lead the development of Graph-Based Associativity Models for scalable entity association.
• Advanced Similarity Matching & Clustering
• Develop and refine matching algorithms using techniques like Fuzzy Matching, Levenshtein Distance, and BERT embeddings.
• Implement Approximate Nearest Neighbor (ANN) algorithms for fast and efficient similarity detection.
• Apply contextual clustering techniques to improve entity recognition systems and enhance model accuracy.
• Machine Learning & Transformer-Based Models
• Build, train, and optimize transformer-based NER models for high-fidelity language understanding.
• Apply Luhn’s algorithm and other heuristic methods to refine large-scale text summarization and keyword extraction tasks.
• Team Collaboration & Documentation
• Collaborate with cross-functional teams to ensure seamless integration of advanced data science solutions into business processes.
• Maintain thorough and precise documentation of methodologies, algorithms, and project findings.
  

Qualifications

• Experience: 4 years of professional industry experience with advanced level data science and deep learning.
• Education: Recently graduated with a Master’s degree in Computer Science, Data Science, or Distributed Systems (completed).
• Technical Expertise:
• Advanced expert-level proficiency in Java and Python for implementing large-scale AI, distributed systems, and data science solutions.
• Demonstrated expertise in regex for handling complex data parsing scenarios.
• Proven mastery of BeautifulSoup, XPath-based heuristics, and DOM parsing for data extraction.
• Advanced skills in headless browsers such as Selenium, Puppeteer, and Playwright.
• Extensive experience with SpaCy, including custom NER pipelines and transformer-based NLP models.
• In-depth knowledge of graph databases such as Neo4j or JanusGraph, and advanced graph algorithms.
• Proficiency in Graph Neural Networks (GNNs) for high-level entity disambiguation and relationship modeling.
• Expertise in contextual embeddings and similarity algorithms like Levenshtein Distance and Fuzzy Matching.
• Strong experience in version control using Git, and collaborative development using GitHub.
• Time Commitment:
• MUST BE ABLE TO DEDICATE AT LEAST 30 HOURS PER WEEK TO THIS POSITION.
• MUST BE ABLE TO STAY AT THE COMPANY FOR AT LEAST 6 MONTHS.
  

Benefits

• Remote native; Location freedom
• Professional industry experience in the SaaS and AI industry
• Creative freedom
• Potential to convert into a full-time position
  
  

Note

This internship offers an exciting opportunity to gain hands-on experience in advanced data science within a high pressure and innovative environment. Candidates must be self-motivated, proactive, and capable of delivering high-quality results independently. The internship provides valuable exposure to cutting-edge technologies and real-world software development practices, making it an ideal opportunity for aspiring senior data scientists.

• This is an unpaid internship at this time and is suitable for new recent Master's graduate candidates that wants to be a Senior Deep Learning Engineers.***
  
  

Please send resumes to services_admin@flowai.tech