{"id":1550824,"url":"https://alion.io/job/nice-staff-machine-learning-engineer","title":"Staff Machine Learning Engineer","company":{"id":6234,"name":"NICE","domain":"nice.com","url":"https://alion.io/company/nice","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"A","score":88,"open_postings":20,"ghost_share":0,"stale_share":0.45,"repost_share":0.05,"time_to_fill_p50_days":59,"computed_at":"2026-10-01T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"staff","employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Sandy, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":155000,"max_usd":321000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":618},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Docker","optional":false},{"name":"Fine-tuning","optional":false},{"name":"GCP","optional":false},{"name":"Knowledge Distillation","optional":false},{"name":"Machine Learning","optional":false},{"name":"Model Distillation","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Quantization","optional":false},{"name":"TensorFlow","optional":false},{"name":"Text-to-Speech","optional":false}],"status":"live","first_seen_at":"2026-09-30T19:18:23Z","employer_posted_date":"2026-09-30","last_verified_at":"2026-10-02T00:40:20Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"At NiCE, we don’t limit our challenges. We challenge our limits. Always. We’re ambitious. We’re game changers. And we play to win. We set the highest standards and execute beyond them. And if you’re like us, we can offer you the ultimate career opportunity that will light a fire within you.\nSo what is the role about?\nNiCE is looking for a Staff Machine Learning Engineer to join NiCE Labs Research (NLR), the team responsible for model expertise and agent architecture for the Cognigy platform. You will evaluate and optimize AI models across Cognigy's agentic systems, including speech models (text-to-speech and speech-to-speech). You will track the model landscape, identify state-of-the-art candidates, and develop strategies to improve quality and latency while reducing cost. You will work closely with NLR colleagues to extend the team's evaluation framework and build proof-of-concept implementations that demonstrate your recommendations.\nHow will you make an impact?\nMonitor the field for new state-of-the-art models and assess their relevance to Cognigy use cases; stay current on advances in ML, model optimization, and agentic AI.\nDesign and run model evaluations, including human-judged protocols for generated output and validation of automated metrics against human ratings.\nDesign and execute optimization strategies (fine-tuning, quantization, distillation, efficient inference) to improve quality, reduce latency, and lower cost.\nDeploy and benchmark open-weight models on cloud platforms and compare platforms for hosting.\nProvide technical review and guidance on teammates' model optimization work.\nCommunicate results and recommendations to technical and non-technical stakeholders.\nHave you got what it takes?\nMS in computer science, machine learning, data science, or a related field.\n3+ years of post-graduate, hands-on experience with ML models, including training, fine-tuning, and evaluation.\nExperience with model optimization techniques such as quantization, distillation, or efficient inference.\nExperience designing evaluations or benchmarks for AI systems, including subjective or human-rated measures.\nProficiency in Python and PyTorch or TensorFlow.\nExperience with cloud ML infrastructure (AWS, Azure, or GCP) for model testing and deployment.\nAbility to build working relationships with cross-functional teams, keep pace with a fast-changing field and shifting priorities, and present clearly to internal and external stakeholders.\nYou will have an advantage if you have:\nExperience evaluating or fine-tuning TTS or S2S models for production use, or related audio and speech work.\nExposure to agentic AI frameworks or conversational AI platforms.\nDocker, microservice deployment, and GPU inference serving.\nWhat’s in it for you?\nJoin an ever-growing, market disrupting, global company where the teams - comprised of the best of the best - work in a fast-paced, collaborative, and creative environment! As the market leader, every day at NiCE is a chance to learn and grow, and there are endless internal career opportunities across multiple roles, disciplines, domains, and locations. If you are passionate, innovative, and excited to constantly raise the bar, you may just be our next NICEr!\nEnjoy NiCE-FLEX!\nAt NiCE, we work according to the NiCE-FLEX hybrid model, which enables maximum flexibility: 2 days working from the office and 3 days of remote work, each week. Naturally, office days focus on face-to-face meetings, where teamwork and collaborative thinking generate innovation, new ideas, and a vibrant, interactive atmosphere.\n\nRequisition ID: 11790\nReporting into: Director, Engineering, AI Research, NiCE Labs\nRole Type: Individual Contributor\n About NiCE\nNICE Ltd. (NASDAQ: NICE) software products are used by 25,000+ global businesses, including 85 of the Fortune 100 corporations, to deliver extraordinary customer experiences, fight financial crime and ensure public safety. Every day, NiCE software manages more than 120 million customer interactions and monitors 3+ billion financial transactions. \nKnown as an innovation powerhouse that excels in AI, cloud and digital, NiCE is consistently recognized as the market leader in its domains, with over 8,500 employees across 30+ countries. \nNiCE is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, age, sex, marital status, ancestry, neurotype, physical or mental disability, veteran status, gender identity, sexual orientation or any other category protected by law.","description_format":"text","description_chars":4594,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"master","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial Intelligence","Professional Services","AI Agents","Call Center Services"],"lifecycle":[{"event":"open","at":"2026-10-01T00:11:35Z"}],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":0,"expected_fill_days":59,"reasons":["conf:5","velocity","win:early","comp:brand"],"computed_at":"2026-10-01T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/nice-staff-machine-learning-engineer","json_url":"https://alion.io/job/nice-staff-machine-learning-engineer.json","meta":{"generated_at":"2026-10-02T01:49:04Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":2343,"day_limit":5000,"remaining_today":2657,"minute_limit":60,"resets_at":"2026-10-03T00:00:00Z"}}}