📍India
Machine Learning Research Engineer III

Technergetics
💵 $90k-$135k
📍Remote
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Summary
Join Technergetics as a Machine Learning Research Engineer III and design, deploy advanced AI capabilities. You will build intelligent systems transforming unstructured and structured data into actionable knowledge, connected via a knowledge graph. Develop and integrate NER, topic modeling, correlation algorithms, and a recommendation system to link insights across domains. This role involves building ML pipelines, scalable ingestion systems, and integrating ML outputs into full-stack applications. The position requires collaboration with a high-performing team and contributing to proposal writing for new opportunities. Remote work is possible, and the salary range is $90,000-$135,000 annually.
Requirements
- Graduation from an accredited college or university with a Master’s degree in a computer science, computer engineering or closely related discipline
- At minimum two years 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
Responsibilities
- 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
- Contribute to or lead proposal writing for new opportunities with government R&D organizations and/or commercial companies for projects within the scope of your expertise
- Apply your technical expertise to become an AI subject matter expert for small teams of researchers and engineers on advanced R&D projects funded by government and commercial customers
Preferred Qualifications
- A PhD in a computer science, computer engineering or closely related discipline
- 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.)
Benefits
- Health, life, disability, dental, and vision insurance coverage
- A 401(k) policy with a 3% company contribution & 3% company match
- Paid Time Off (including a PTO “gift day” for your birthday)
- 11 Federal Holidays per year
- Three weeks paid maternity/paternity leave
- Annual technology “allowances”
- Referral bonuses
- Professional recognition awards
- Healthcare stipends
- Tuition/education reimbursement (once specific requirements are met)
- Flexible daily start and stop times for most projects and positions
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