{"id":2641097,"url":"https://alion.io/job/src-inc-aiml-engineer","title":"AI/ML Engineer","company":{"id":2417477,"name":"SRC, Inc.","domain":"srcinc.com","url":"https://alion.io/company/srcinc","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Jobvite","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["New York, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":70000,"max":96000,"currency":"USD","period":"year","gross":null,"usd_annual":96000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"Axolotl","optional":false},{"name":"Docker","optional":false},{"name":"DPO","optional":false},{"name":"DVC","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Git","optional":false},{"name":"GRPO","optional":false},{"name":"Gymnasium","optional":false},{"name":"Hugging Face","optional":false},{"name":"LLM","optional":false},{"name":"LLM Evaluation","optional":false},{"name":"LoRA","optional":false},{"name":"Machine Learning","optional":false},{"name":"Matplotlib","optional":false},{"name":"MLFlow","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Multimodal AI","optional":false},{"name":"NumPy","optional":false},{"name":"PEFT","optional":false},{"name":"Post-training","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"QLoRA","optional":false},{"name":"RAG","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"Scikit-learn","optional":false},{"name":"SFT","optional":false},{"name":"Stable-Baselines3","optional":false},{"name":"Structured Outputs","optional":false},{"name":"Time Series Forecasting","optional":false},{"name":"Tool Use","optional":false},{"name":"Transformers","optional":false},{"name":"TRL","optional":false},{"name":"Unsloth","optional":false},{"name":"Weights & Biases","optional":false}],"status":"live","first_seen_at":"2026-10-15T18:53:29Z","employer_posted_date":"2026-10-15","last_verified_at":"2026-10-16T19:45:41Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"SRC, Inc. is currently seeking an AI/ML Engineer to join a team building machine learning and generative AI capabilities for defense and national security missions. This is a hands-on, early-career engineering role focused on the practical work of turning data into working models: assembling and curating datasets, training and fine-tuning models, and building the evaluation harnesses that tell us whether a model is actually good enough to field. You will work under the direction of senior engineers and scientists on tasks scoped within larger programs, with increasing ownership of discrete technical tasks as you develop. The work spans classical machine learning, deep learning, reinforcement learning, and the rapidly evolving generative AI toolchain, applied to real sensor data and real mission problems in ISR, EW, and advanced sensing. This is a strong fit for an engineer who wants to build depth in applied ML on problems where the data is messy, the ground truth is hard-won, and the results have to hold up under scrutiny.\nWhat You'll Do\nBuild, clean, label, and version datasets from real and simulated sources, including handling class imbalance, distribution shift, and sparse or noisy labels\nTrain, fine-tune, and benchmark models using standard open-source frameworks, running experiments as assigned and documenting results clearly\nDevelop and run evaluation pipelines - task-specific metrics, held-out and adversarial test sets, regression suites - and report findings honestly, including negative results\nSupport generative AI efforts through prompt development and iteration, structured output design, retrieval-augmented generation pipelines, and comparative evaluation of open-weight and commercial language models\nAssist with parameter-efficient fine-tuning (LoRA/QLoRA) and supervised fine-tuning of open-weight models for domain-specific tasks\nImplement reinforcement learning experiments in standard environments and instrument them for reproducible measurement\nMaintain reproducible experiment tracking, environment configuration, and code hygiene so that results can be regenerated by others\nContribute data, figures, and written findings to technical reports, program reviews, and oral presentations\nCollaborate with algorithm engineers and domain experts to understand the sensor data and physical phenomenology behind the datasets you work with\nWhat You'll Bring\nBachelor’s in computer science, Engineering, Mathematics, Physics, Statistics, or a related technical discipline and 0+ years of experience (internships, co-ops, research assistantships, and substantial academic project work count)\nWorking proficiency in Python and the core scientific stack (NumPy, pandas, scikit-learn, matplotlib)\nFamiliarity with at least one deep learning framework, preferably PyTorch\nExposure to the Hugging Face ecosystem (Transformers, Datasets, Tokenizers) or equivalent open-source model tooling\nUnderstanding of ML fundamentals: train/validation/test discipline, overfitting and regularization, cross-validation, and the metrics appropriate to classification, regression, detection, and generation tasks\nComfort with Git-based collaborative development\nClear written and verbal communication, and a willingness to say when a result doesn't hold up\nWays to Stand Out\nExperience fine-tuning open-weight language models using PEFT methods (LoRA, QLoRA) or the TRL/Axolotl/Unsloth toolchain\nHands-on work with RAG systems: embedding models, vector stores, chunking strategies, and retrieval evaluation\nFamiliarity with LLM evaluation practice - LLM-as-judge, rubric-based grading, eval harness design, and the failure modes of each\nExperience with experiment tracking and data versioning tools (Weights & Biases, MLflow, DVC)\nExposure to reinforcement learning libraries (Gymnasium, Stable-Baselines3, CleanRL) or to preference-based post-training methods (DPO, GRPO)\nExperience with agentic workflows, tool-calling, or the Model Context Protocol (MCP)\nWork with non-natural-image modalities: RF, radar, SAR, audio, time series, or multimodal data\nContainerization (Docker) and experience running jobs on GPU clusters or cloud compute\nMaster's degree in a related technical discipline\nWhat Sets Us Apart?\nSRC, Inc., a not-for-profit research and development company, combines information, science, technology and ingenuity to solve “impossible” problems in the areas of defense, environment and intelligence. Across our family of companies, we apply bright minds, fresh thinking and relentless determination to deliver innovative products and services that are redefining possible®. When you join our team, you’ll be a part of something truly meaningful - helping to keep America and its allies safe and strong. You’ll collaborate with more than 1,400 engineers, scientists and professionals - with 20 percent of those employees having served in the military - in a highly innovative, inclusive and equitable work environment. You’ll receive a competitive salary and comprehensive benefits package that includes four or more weeks of paid time off to start, 10 percent employer contribution toward retirement, and 100 percent tuition support.\nTotal compensation for this role is market competitive. The anticipated salary range for this position based out of Dayton, OH is estimated at $70,000 to $96,000 annually. The actual salary will vary based on applicant’s experience, skills, and abilities, geographic location as well as other business and organizational needs. SRC offers competitive benefit options, for more details please visit our website.\nNon-Discrimination Statement\nIndividuals seeking employment are considered without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or age, or status as a protected veteran or disability except as strictly required by applicable law. You are being given the opportunity to provide the following information in order to help us comply with federal and state record keeping, reporting, and other legal requirements, including requirements under Section 503 of the Rehabilitation Act, 29 U.S.C. 793, and the Vietnam Era Veterans’ Readjustment Assistance Act (VEVRAA), 38 U.S.C. 4212.\nLearn more about SRC:\nAbout Us\nEmployee Benefits\nAwards & Recognition\nSecurity Clearance\nLocation\nSyracuse,\nNew York\nFairborn,\nOhio\n\n Employment Type Full-Time Salaried\n Experience Required 0+ Years\n Education Required Bachelors Degree\n Security Clearance Requirement Must meet eligibility requirements\n Travel % 10","description_format":"text","description_chars":6518,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Military","Higher Education","Nonprofits & Foundations"],"lifecycle":[{"event":"open","at":"2026-10-15T18:53:29Z"}],"visa":[],"liveness":{"score":99,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.993,"p_room":1,"age_days":0,"expected_fill_days":9,"reasons":["conf:3","urgency","velocity","win:early"],"computed_at":"2026-10-16T05:45:00Z"},"pay":{"stated_usd_annual":96000,"is_top_pay":false},"html_url":"https://alion.io/job/src-inc-aiml-engineer","json_url":"https://alion.io/job/src-inc-aiml-engineer.json","meta":{"generated_at":"2026-10-16T23:35:40Z","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":5578,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-17T00:00:00Z"}},"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":2417477},"rest":"https://alion.io/mcp/rest/get_company?id=2417477"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fsrc-inc-aiml-engineer"},{"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%2Fsrc-inc-aiml-engineer"},{"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%2Fsrc-inc-aiml-engineer"},{"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/src-inc-aiml-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fsrc-inc-aiml-engineer"}]}