{"id":57783,"url":"https://alion.io/job/jumio-machine-learning-engineer-iv-biometrics","title":"Machine Learning Engineer - IV (Biometrics)","company":{"id":1258,"name":"Jumio","domain":"jumio.com","url":"https://alion.io/company/jumio","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"B","score":70,"open_postings":4,"ghost_share":0.25,"stale_share":0.25,"repost_share":0.25,"time_to_fill_p50_days":77,"computed_at":"2026-10-17T05:46:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India","India"],"countries":["IN"],"hiring_countries":["IN"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":23000,"max_usd":51000,"period":"year","method":"role_seniority_country_cell","sample_n":37},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon EC2","optional":false},{"name":"Amazon EKS","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"AWS","optional":false},{"name":"Computer Vision","optional":false},{"name":"JAX","optional":false},{"name":"Knowledge Distillation","optional":false},{"name":"Machine Learning","optional":false},{"name":"Model Distillation","optional":false},{"name":"ONNX","optional":false},{"name":"OpenCV","optional":false},{"name":"Pillow","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Quantization","optional":false},{"name":"Synthetic Data","optional":false},{"name":"TensorFlow","optional":false},{"name":"TensorRT","optional":false},{"name":"Core ML","optional":true},{"name":"Diffusion Models","optional":true},{"name":"FAISS","optional":true},{"name":"Kubernetes","optional":true},{"name":"LiteRT","optional":true},{"name":"Milvus","optional":true},{"name":"TFLite","optional":true}],"status":"live","first_seen_at":"2026-02-23T13:02:07Z","employer_posted_date":"2026-07-31","last_verified_at":"2026-10-17T09:11:56Z","board_verified":true,"closed_at":null,"days_open":235,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":235},"description":"Role Purpose\nWe’re looking for a Staff/Senior Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process.\nWhat You’ll Do\nLead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition)\nRigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions.\nArchitect, train, and optimize models using PyTorch, Tensorflow, and/or JAX\nOwn and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps.\nProduction Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS.\nMentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team.\nWhat We’re Looking For\nExperience: 5+ years of industry experience in Machine Learning, with at least 3 years dedicated to Biometrics or Face Analysis.\nDeep expertise in computer vision and biometrics, especially face recognition.\nFairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact.\nStrong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code.\nSystems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like Airflow.\nCloud Native: Hands-on experience scaling training jobs on multi-GPU clusters and deploying services on AWS (SageMaker, EC2, EKS).\nNice to Have\nResearch Publications: Papers in CVPR, ICCV, ECCV, or FG related to face recognition, image quality assessment, or fairness.\nLarge Scale Search: Experience with vector databases (e.g., Milvus, Faiss) and approximate nearest neighbor (ANN) search algorithms.\nFamiliarity with privacy, security, and compliance in biometric systems.\nMobile/Edge Experience: Experience porting models to edge or mobile devices utilizing frameworks such as CoreML, LiteRT, and/or TFLite.\nSynthetic Data: Experience using GANs or diffusion models to generate synthetic faces for training.\nStrong communication skills.\nJumio Values:\nIDEAL: Integrity, Diversity, Empowerment, Accountability, Leading Innovation\nEqual Opportunities:\nJumio is a collaboration of people with different ideas, strengths, interests and cultures. We welcome applications and colleagues from all backgrounds and of all statuses.\nAbout Jumio:\nJumio is a B2B technology company dedicated to eradicating online identity fraud, money laundering and other financial crimes to help make the internet safer. We leverage AI, biometrics, machine learning, liveness detection and automation to create solutions that are trusted by leading brands worldwide and respected by industry thought leaders. \nJumio is the leading provider of online identity verification, eKYC and AML solutions. With a global footprint, we’re expanding the team to meet strong client demand across a range of industries including Financial Services, Travel, Sharing Economy, Fintech, Gaming, and others.\nApplicant Data Privacy\nWe will only use your personal information in connection with Jumio’s application, recruitment, and hiring processes, as described in Jumio’s Applicant Privacy Notice. 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