{"id":800443,"url":"https://alion.io/job/technergetics-aiml-engineer-iii","title":"AI/ML Engineer III","company":{"id":720761,"name":"Techngs","domain":"techngs.com","url":"https://alion.io/company/techngs","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":["Rome, United States"],"countries":["US"],"hiring_countries":["US","IT"],"hiring_countries_total":2,"salary":{"min":125000,"max":175000,"currency":"USD","period":"year","gross":null,"usd_annual":175000},"salary_estimate":null,"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"Agile","optional":false},{"name":"AI Agents","optional":false},{"name":"Arize Phoenix","optional":false},{"name":"AutoGen","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"CrewAI","optional":false},{"name":"Docker","optional":false},{"name":"Edge AI","optional":false},{"name":"FAISS","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Function Calling","optional":false},{"name":"GCP","optional":false},{"name":"GitLab","optional":false},{"name":"Hugging Face","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"Knowledge Distillation","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangChain","optional":false},{"name":"Langfuse","optional":false},{"name":"LangGraph","optional":false},{"name":"LangSmith","optional":false},{"name":"Linux","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"LoRA","optional":false},{"name":"Machine Learning","optional":false},{"name":"Milvus","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Model Distillation","optional":false},{"name":"Multimodal AI","optional":false},{"name":"Ollama","optional":false},{"name":"ONNX Runtime","optional":false},{"name":"PEFT","optional":false},{"name":"pgvector","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Pydantic AI","optional":false},{"name":"Pytest","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Qdrant","optional":false},{"name":"Quantization","optional":false},{"name":"RAG","optional":false},{"name":"Rest API","optional":false},{"name":"Scrum","optional":false},{"name":"State Management","optional":false},{"name":"Structured Outputs","optional":false},{"name":"TensorRT-LLM","optional":false},{"name":"Triton Inference Server","optional":false},{"name":"vLLM","optional":false},{"name":"Weaviate","optional":false},{"name":"C++","optional":true},{"name":"DeepSpeed","optional":true},{"name":"Django","optional":true},{"name":"FSDP","optional":true},{"name":"GraphRAG","optional":true},{"name":"Java","optional":true},{"name":"JavaScript","optional":true},{"name":"Knowledge Graph","optional":true},{"name":"PostgreSQL","optional":true},{"name":"Ray","optional":true},{"name":"React Native","optional":true},{"name":"React.js","optional":true},{"name":"SLURM","optional":true},{"name":"TensorRT","optional":true},{"name":"Transformers","optional":true}],"status":"live","first_seen_at":"2026-08-20T18:23:04Z","employer_posted_date":"2026-08-20","last_verified_at":"2026-11-06T10:31:15Z","board_verified":true,"closed_at":null,"days_open":77,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":77},"description":"AI/ML Engineer III\nTechnergetics - Utica/Rome, NY area\n\nA Note About Our AI-Assisted Interview Process\nWe use an AI application, “Alex Taylor,” to conduct first-round interviews for this position. The interview takes approximately 35 minutes. If we would like to interview you, you will receive an email invitation from “Alex” within ten business days of your application.\nAlex is available 24/7, which lets us conduct far more first-round interviews than our human staff's schedule alone would allow. Technergetics HR (and additional staff, as applicable) reviews every first-round interview. AI supports our decision-making, but all decisions about who advances to a first or second interview are made by our human staff. Candidates selected for a second-round interview will meet with the HR director and hiring manager.\nAny data collected during the interview process, including AI-generated insights, is handled with care and confidentiality, in compliance with applicable data protection laws. Your responses are processed only to provide feedback on your skills and knowledge. Data is stored securely and will not be shared with third parties without your consent.\nWe understand some candidates may be hesitant to interview with an AI application - it is by no means perfect at this time. But as a company dedicated to research and development in AI/ML and other technologies, we see this as a chance to practice what we preach.\n\nOpportunity Overview\nTechnergetics is looking for an AI/ML Engineer III to design, develop, and deploy advanced AI capabilities alongside a high-performing team of full-stack developers. This role centers on building production systems around foundation models, including agentic workflows, retrieval-augmented generation, and multimodal machine learning, for demanding government and commercial customers.\nContingent Position: This position is contingent upon contract award and funding.\nPosition Details\nSalary Range: $125,000-$175,000 annually. The final offer depends on how many position qualifications the candidate meets, as well as education and experience. This is a full-time, exempt position.\nLocation, Travel, and Remote Work\nCandidates who are located within, or relocate to, a commutable distance of the Utica/Rome area can expect to be onsite 20% of their workweek, for access to company and AFRL (Air Force Research Lab) facilities, secure data, and customers. A relocation signing bonus may be available.\nRemote candidates outside a commutable distance to Utica/Rome will still be considered but may need to travel to the Utica/Rome area quarterly or more often, depending on company and client needs.\nThis position also involves approximately 5%-10% travel to customer and client sites outside the Utica-Rome, NY area.\nDue to the security clearance required for this position, only U.S. citizens are eligible to apply, per Executive Order 12968 (Access to Classified Information).\nResponsibilities and Duties\nThe successful candidate will work on one or more of our Machine Learning (ML) software products, with day-to-day activities that include:\nLeading the design, development, and deployment of multi-modal machine learning architectures, including models and algorithms, to solve complex mission and business problems\nDesigning and building agentic systems on top of large language models for operational deployment\nImplementing retrieval-augmented generation pipelines that ground model outputs against authoritative data sources\nDefining and running evaluation for model and agent behavior in production\nOptimizing model inference for production and edge/DDIL (denied, degraded, intermittent, and limited bandwidth) deployment scenarios\nApplying AI assurance practices and documenting model limitations to support accreditation and customer review\nIntegrating state-of-the-art machine learning libraries, foundation models, and agent frameworks into existing software applications\nDeveloping and maintaining data pipelines and supporting software for collecting, preprocessing, and transforming data for machine learning tasks\nDesigning software solutions, algorithms, and cloud architectures needed to satisfy product features and functionality defined by the product owner and other stakeholders in a production environment\nLeading, coaching, and mentoring junior data scientists, engineers, and other staff\nContributing to phases of the software development life cycle, including functional analysis, technical requirements, technical design, prototyping, coding, testing, deployment, data migration, and support\nParticipating in daily scrums and working with the scrum master and scrum team to organize and prioritize workload through story-pointing, supporting delivery timelines and priorities\nCollaborating with cross-functional teams to understand business requirements and translate them into machine learning solutions\nPerforming unit testing and debugging to identify and fix software defects, and contributing to code reviews with constructive feedback to peers\nStaying current on new AI/ML approaches, frameworks, and industry trends\nServing as an AI subject matter expert for small teams of researchers and engineers on advanced R&D projects funded by government and/or commercial customers, and contributing to or leading proposal writing for new opportunities within your area of expertise\nEducation and Certifications\nThis position generally requires a Master’s degree from an accredited college or university in computer science, computer engineering, artificial intelligence, machine learning, or a closely related discipline. A Ph.D. in one of these fields is strongly preferred. A Bachelor’s degree in one of these fields, combined with seven or more years of directly relevant professional experience, will be considered in lieu of a Master’s degree.\nQualifications\nExperience and Foundational Engineering\nAt minimum, three years of professional experience in machine learning or AI systems engineering, including at least one year building with large language models or other foundation models in a production setting\nStrong proficiency in Python, including asynchronous programming and modern packaging and dependency management\nWorking knowledge of server-side development (API definitions, REST services, streaming and asynchronous services, etc.)\nFluency with containerization and deployment frameworks such as Kubernetes or Docker, including GPU scheduling and resource management for training and inference workloads\nHands-on work with at least one major cloud platform (AWS, Azure, or Google Cloud)\nComfort with Linux platforms and command-line environments\nFamiliarity with Continuous Delivery/Continuous Integration (DevSecOps, GitLab Pipelines, etc.)\nProficiency with automated testing in Python (pytest), including regression suites for non-deterministic model and agent behavior\nArtificial Intelligence and Machine Learning\nDemonstrated ability to train and deploy machine learning models with PyTorch and the Hugging Face ecosystem (transformers, datasets, accelerate)\nA track record of building applications on top of large language models, including prompt engineering, structured output, and context management\nFluency with agentic frameworks and patterns such as LangGraph, LangChain, CrewAI, AutoGen, Pydantic AI, or vendor agent SDKs, including multi-step tool use, planning, memory, and state management, and with integrating models, tools, and data sources through open standards such as Model Context Protocol (MCP)\nPractical command of retrieval-augmented generation, including chunking and embedding strategy, vector databases (pgvector, Milvus, Qdrant, Weaviate, FAISS), and hybrid or re-ranked retrieval\nAbility to design and run LLM evaluation, including task-specific benchmarks, golden datasets, LLM-as-judge methods, and tracing and observability tooling (LangSmith, Langfuse, Arize, Weights & Biases)\nCommand of model adaptation techniques including fine-tuning, LoRA/PEFT, quantization, and distillation, and the judgment to know when adaptation is preferable to prompting or retrieval\nProven ability to serve models in production with inference frameworks such as vLLM, TensorRT-LLM, Triton Inference Server, Ollama, or ONNX Runtime, including latency, throughput, and cost tradeoffs, as well as deployment to edge or resource-constrained environments, including on-device inference\nGrounding in AI safety and assurance practices, including guardrails, input and output filtering, prompt injection mitigation, and human-in-the-loop design\nDirect work with multimodal models and cross-modal embedding across text, imagery, video, audio, or geospatial data\nLeadership and Collaboration\nDemonstrated leadership on technical tasks and/or technical teams, including Agile software development and leading one or more tasks to completion\nExcellent communication and teamwork skills, including the ability to explain technical tradeoffs to non-technical stakeholders and customers\nNice to Have\nExposure to DoD cloud and software factory environments such as Platform One, BESPIN, AF Cloud One, DAF CLOUDworks, or AWS GovCloud, and with ATO and RMF processes at IL4/IL5\nFamiliarity with DoD and federal AI policy and governance, including CDAO Responsible AI guidance\nWork with distributed training frameworks and schedulers (DeepSpeed, FSDP, Ray, Slurm)\nKnowledge of knowledge graphs, ontologies, or Resource Description Framework (RDF), particularly as applied to graph-based retrieval (GraphRAG) and grounding\nBackground in developing modern full-stack web applications with frameworks such as Node, React, React Native, or Django\nBasic working knowledge of Go, Java, C++, or other compiled languages\nContributions to open source AI/ML projects, or published applied AI research\nClearance\nSelected applicants will undergo a security investigation and must meet and maintain eligibility for, at minimum, Top Secret access to classified information.\nBenefits\nOur benefits package includes health, life, disability, dental, and vision insurance, plus a 401(k) plan with a 3% company contribution and 3% company match.\nAdditional perks include:\nGenerous Paid Time Off, including a PTO “gift day” for your birthday\n11 federal holidays per year\nThree weeks of paid maternity/paternity leave\nAnnual technology allowance\nReferral bonuses and professional recognition awards\nHealthcare stipends\nTuition/education reimbursement (once eligibility requirements are met)\nFlexible daily start and stop times for most projects and positions\nCompany Description\nTechnergetics is a U.S.-based company headquartered in Utica, NY, with employees and clients located throughout 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 more.\n\nBeware of Fraudulent Job Offers and Postings\nTechnergetics will never extend an offer of employment without a thorough interview process that includes a face-to-face interview - either in person or via a virtual Teams meeting - from an official Technergetics email address (@techngs.com). If you receive correspondence from any other email address, it is a scam. \n\nTechnergetics does not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.","description_format":"text","description_chars":11618,"description_truncated":false,"requirements":{"experience_years_min":7,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":true,"languages":[]},"benefits":["Vision insurance"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"},{"name":"Italy","iso":"IT","kind":"country"}],"hiring_excludes":[],"relocation_offered":true,"industries":["IT Consulting & Digital Transformation","Custom Software Development"],"lifecycle":[{"event":"open","at":"2026-09-12T07:26:32Z"}],"visa":[],"liveness":{"score":14,"band":"cold","label":"Long shot","p_open":1,"p_active":0.502,"p_room":0.28,"age_days":77,"expected_fill_days":28,"reasons":["conf:4","win:tail","crowd:"],"computed_at":"2026-11-06T05:58:05Z"},"pay":{"stated_usd_annual":175000,"is_top_pay":false},"html_url":"https://alion.io/job/technergetics-aiml-engineer-iii","json_url":"https://alion.io/job/technergetics-aiml-engineer-iii.json","meta":{"generated_at":"2026-11-06T11:28:51Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":20885,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-11-07T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":720761},"rest":"https://alion.io/mcp/rest/get_company?id=720761"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Ftechnergetics-aiml-engineer-iii"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Ftechnergetics-aiml-engineer-iii"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Ftechnergetics-aiml-engineer-iii"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/technergetics-aiml-engineer-iii\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Ftechnergetics-aiml-engineer-iii"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":800443}},{"tool":"search_jobs","arguments":{"company":"techngs.com","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":800443},"note":"people open to offers who fit this vacancy"}],"note":"The same data through MCP tools: https://alion.io/mcp/open needs no sign-in (compact searches, postings, people); https://alion.io/mcp with an Alion account has everything. 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