Machine Learning Research Engineer II

Job description

Artificial Intelligence Disclaimer:

Technergetics employs “Alex Taylor” an Artificial Intelligence interview app for the initial (first round) interview for this position, meaning if you are chosen for a first round interview, “Alex” will interview you. “Alex” is available to schedule first round interviews ²⁴⁄₇ and allows us to conduct a much greater number of first round interviews than our human staff’s availability would allow. You will receive an email with scheduling instructions from [email protected] within approximately 5 days of your application if we would like to hold a first round interview with you. Please check your spam or junk folders for correspondence from “Alex”. All first round interviews are reviewed by Technergetics recruiting and software engineering staff.

While AI is a tool to help us improve our interview process, the decision-making power remains with human recruiters and hiring managers. Candidates who pass the first round interview with “Alex” and are chosen for second round interviews meet with human recruiters and engineers. Any data collected during the interview process, including AI-generated insights, will be handled with utmost care and confidentiality. We will comply with all applicable data protection laws and regulations. Your responses will be processed by an AI system to provide feedback on your skills and knowledge. We want to assure you that this data will be stored securely and will not be shared with any third parties without your consent.

Beware of fraudulent job offers and postings!

Technergetics will never extend an offer of employment without a thorough interview process involving face to face interviews either in-person or a virtual Teams meeting from an official Technergetics email address ( @techngs.com). If you receive any correspondence from an email other than techngs.com, it is a scam. Pre-interview code testing is only administered through the Codility platform. We will not send out questionnaires or testing through any other platform/site prior to a first interview.

Opportunity Overview:

Technergetics is looking for a Machine Learning Research Engineer II to design and deploy advanced AI capabilities alongside a high-performing team of full stack developers. This role focuses on building intelligent systems that transform unstructured documents and structured system data into actionable knowledge, connected via an evolving knowledge graph.

This position will develop and integrate named entity recognition (NER), topic modeling, correlation algorithms, and a recommendation system to link extracted insights across domains—powering intelligent applications for decision support, analytics, and automation.

Position Details

Salary Range: $90,000-$125,000 annually. The successful candidate’s salary will depend on how many position qualifications the candidate meets, in addition to education and experience. This is a full-time exempt position.

Location/Travel/Remote Performance:

Remote performance is possible for this position and Technergetics will consider candidates from across the United States. A successful candidate living in the Utica-Rome area will have remote options and may occasionally be required to attend meetings or work in-person in Utica-Rome facilities. Travel to client sites is not expected in this position.

Due to the clearance required for this position, only U.S. citizens are eligible to apply; as outlined in Executive Order 12968: Access to Classified Information, eligibility for access to classified information may only be granted to employees who are United States citizens.

Responsibilities and Duties

The day-to-day activities of this position are working within the project team to:

• Design and implement ML pipelines to extract entities, topics, and relationships from unstructured text (e.g., PDFs, reports) and structured data sources
• Build scalable ingestion systems for integrating document-based and API-driven data streams into a unified context layer
• Apply and fine-tune NER, topic modeling, and clustering techniques using modern frameworks (spaCy, HuggingFace, scikit-learn, etc.)
• Correlate and link extracted data into a graph-based knowledge representation using platforms like Memgraph or Neo4j
• Develop and deploy recommendation systems to suggest relevant content, actions, or knowledge graph entities based on user profiles, extracted insights, or contextual cues
• Implement LLM-powered search capabilities that leverage embeddings, vector databases, and semantic understanding for intelligent querying across documents and graph data
• Integrate ML outputs into full-stack applications built on React, Go, GraphQL, and PostgreSQL
• Work with LangChain and LLM APIs (OpenAI, vLLM, Ollama) to enrich query capabilities and agent reasoning
• Collaborate with infrastructure engineers to containerize and automate deployments via Docker and GitLab CI/CD

Education and Certifications:

This project requires, at minimum, graduation from an accredited college or university with a bachelor’s degree in a computer science, computer engineering or closely related discipline.

Qualifications:

• At minimum one year of experience building and deploying ML solutions
• Strong Python skills with experience in ML/NLP libraries (e.g., spaCy, HuggingFace Transformers, scikit-learn)
• Hands-on experience with named entity recognition (NER), topic modeling, and document classification
• Experience working with unstructured and structured data sources at scale
• Familiarity with knowledge graphs, graph databases, and entity-relation modeling
• Proven experience building recommendation systems or content-based/personalized ranking algorithms
• Hands-on experience with semantic search, vector indexing, or embedding-based LLM search architectures
• Solid understanding of integrating ML services into larger software systems

Possessing the following knowledge or experience is a plus:

• Experience using LangChain and vector database frameworks in developing retrieval-augmented generation (RAG) pipelines
• Familiarity with backend and infrastructure tools (Go, GraphQL, Docker, GitLab CI/CD)
• Background in deploying AI-powered UIs or intelligent agents in end-user applications
• Exposure to mission-oriented or domain-specific knowledge modeling (e.g., defense, logistics, health, etc.)

Clearance:

Applicants selected will be subject to a security investigation and must meet and maintain eligibility requirements for, at minimum, SECRET access to classified information.

Benefits:

Our benefits package includes health, life, disability, dental, and vision insurance coverage and a 401(k) policy with a 3% company contribution & 3% company match.

Other perks include generous Paid Time Off (including a PTO “gift day” for your birthday), 11 Federal Holidays per year, three weeks paid maternity/paternity leave, and annual technology “allowances”.

Wait! Even more perks include referral bonuses, professional recognition awards, healthcare stipends, tuition/education reimbursement (once specific requirements are met), and flexible daily start and stop times for most projects and positions.

Company Description

Technergetics is a US-based company headquartered in Utica, NY, with employees and clients  located through out the country.  The Utica/Rome area is a hub of cutting-edge cyber technology research, bolstered by the Griffiss Business & Technology Park’s tenants and facilities, including the Air Force Research Lab (AFRL).  At Technergetics, we work with a wide variety of technologies, including mobile and web apps, Quantum computing, machine learning and artificial intelligence, AI-enabled edge devices, and many more.

We do not discriminate on the basis of   race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.