{"id":2505366,"url":"https://alion.io/job/abnormal-machine-learning-engineer-i-message-security-products","title":"Machine Learning Engineer I - Message Security Products","company":{"id":20628,"name":"Abnormal AI","domain":"abnormal.ai","url":"https://alion.io/company/abnormal-ai","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":"junior","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Singapore"],"countries":["SG"],"hiring_countries":["SG"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":46000,"max_usd":94000,"period":"year","method":"role_seniority_country_cell","sample_n":23},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"A/B Testing","optional":false},{"name":"Machine Learning","optional":false},{"name":"AWS","optional":true},{"name":"Databricks","optional":true},{"name":"DLP","optional":true},{"name":"Python","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-07-27T10:33:03Z","employer_posted_date":"2026-09-09","last_verified_at":"2026-10-14T15:05:08Z","board_verified":true,"closed_at":null,"days_open":79,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":79},"description":"About the Role\nAbnormal AI is seeking a Machine Learning Engineer - I (MLE) to join the Misdirected Email Detection (MED) team. The MED team plays a critical role in preventing accidental data loss by detecting and blocking misdirected outbound emails, delivering protection at scale without adding operational burden to customer SOCs.\nThis is a highly applied role for MLEs who thrive on building, iterating, and experimenting. Rather than focusing solely on model training, you will also be responsible for developing practical, end-to-end ML solutions. This includes but is not limited to generating and refining features, testing hypotheses, averaging signals, and translating research ideas into production-grade systems, all while collaborating cross-functionally to turn customer needs into measurable product improvements. The ideal candidate combines a tinkerer's mindset with technical rigor, balancing innovation with production excellence to drive experimentation, scale solutions, and deliver reliable detection capabilities that create meaningful customer impact in real-world environments.\nWhat you will do\nPartner with Product Manager, Tech Lead and engineering stakeholders to align technical deliverables to roadmap milestones and ensure successful GA launches across supported environments.\nOwn the full ML lifecycle for Misdirected Email, including data wrangling, feature engineering, model training and evaluation, deployment, and monitoring. Deliver iterative improvements with measurable reliability and customer impact.\nRun rigorous experiments and evaluations (offline metrics, online A/B testing, post-launch monitoring), set thresholds, and conduct targeted error analysis to prevent regressions.\nCommunicate effectively across time zones, maintain high-quality technical documentation, and contribute to shared team knowledge.\nParticipate in shared on-call rotation for owned components, with responsibilities focused on detection efficacy and realtime scoring systems. Priorities include resolving efficacy-related alerts, investigating high-visibility false positives, and addressing reported false positives/false negatives from customers or internal teams.\nMust Haves\nBS degree in Computer Science, Machine Learning, Artificial Intelligence, Information Systems, or a related engineering or quantitative field.\n1+ years building and operating applied ML features in production systems.\nProven experience contributing to end-to-end ML systems, including data wrangling (text and structured), feature engineering, model selection, training, evaluation, and production deployment with monitoring.\nDemonstrated ability to implement and reason about algorithms, develop features, average and combine signals, and apply numerical computing effectively.\nDemonstrated ability to interrogate production data, identify behavioral or trend shifts, and launch targeted experiments to improve model efficacy.\nUnderstanding of online vs offline pipelines, data tables and labeling workflows to effectively leverage tooling to support safe, scalable model deployments.\nExperience running offline metrics, online A/B tests, setting thresholds, and monitoring drift and performance, with guardrails and rollback strategies to ensure reliable iteration.\nStrong written and asynchronous communication skills. Effective working independently and across distributed, cross-functional teams.\nNice to Have\nExperience with our stack: Python, Go, AWS, Spark, Databricks\nExperience in email security/DLP or misdirected email prevention domains and customer-focused ML deployments.\nExperience writing detectors/rules to complement ML models for safe launches and rapid iteration.\nExperience with operationalising research into reliable, customer-facing systems, with emphasis on scalability, performance, and detection accuracy in real-world environments.\nPrior experience contributing to a small team or project to deliver a feature or component from scratch.\nA note on AI in our process: \n Abnormal AI uses AI-assisted tools to help our recruiting team prepare for candidate interviews. These tools analyze resume content and role requirements to suggest interview questions and areas for the interviewer to explore.They do not make hiring decisions or screen candidates automatically. Every decision about a candidacy is made by a person. Further, if your application is successful and Abnormal AI makes a conditional offer of employment, we will carry out pre-employment checks which must be successfully completed to progress to a final offer. All processes and pre-employment checks are in line with prevailing legislation and Abnormal AI's policies relevant to our security and privacy standards.\nAbnormal AI is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status or other characteristics protected by law. For our EEO policy statement please click here. If you would like more information on your EEO rights under the law, please click here.","description_format":"text","description_chars":5097,"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":[{"name":"Singapore","iso":"SG","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Email Security","Cybersecurity","Fraud Detection","Information Security"],"lifecycle":[{"event":"open","at":"2026-10-14T07:12:31Z"}],"visa":[],"liveness":{"score":9,"band":"cold","label":"Long shot","p_open":1,"p_active":0.321,"p_room":0.28,"age_days":79,"expected_fill_days":27,"reasons":["conf:2","win:tail","crowd:junior"],"computed_at":"2026-10-14T17:38:21Z"},"pay":null,"html_url":"https://alion.io/job/abnormal-machine-learning-engineer-i-message-security-products","json_url":"https://alion.io/job/abnormal-machine-learning-engineer-i-message-security-products.json","meta":{"generated_at":"2026-10-14T17:38:21Z","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":22548,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-15T00:00:00Z"}},"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":20628},"rest":"https://alion.io/mcp/rest/get_company?id=20628"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fabnormal-machine-learning-engineer-i-message-security-products"},{"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%2Fabnormal-machine-learning-engineer-i-message-security-products"},{"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%2Fabnormal-machine-learning-engineer-i-message-security-products"},{"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/abnormal-machine-learning-engineer-i-message-security-products\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fabnormal-machine-learning-engineer-i-message-security-products"}]}