{"id":967762,"url":"https://alion.io/job/hello-heart-machine-learning-engineer-2","title":"Senior Machine Learning Engineer, ML Ops","company":{"id":92864,"name":"Hello Heart","domain":"helloheart.com","url":"https://alion.io/company/hello-heart","size_band":"5000+","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":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Tel Aviv, Israel"],"countries":["IL"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":103000,"max_usd":268000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":2365},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon SageMaker","optional":false},{"name":"AWS","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"GitHub Actions","optional":false},{"name":"Jenkins","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"Vertex AI","optional":false},{"name":"Apache Kafka","optional":true},{"name":"Datadog","optional":true},{"name":"Feast","optional":true},{"name":"Feature Store","optional":true},{"name":"Grafana","optional":true},{"name":"HIPAA","optional":true},{"name":"Kubernetes","optional":true},{"name":"LightGBM","optional":true},{"name":"MLFlow","optional":true},{"name":"Prometheus","optional":true},{"name":"Scikit-learn","optional":true},{"name":"Terraform","optional":true},{"name":"XGBoost","optional":true}],"status":"live","first_seen_at":"2026-08-05T07:25:26Z","employer_posted_date":"2026-10-25","last_verified_at":"2026-11-04T23:28:10Z","board_verified":true,"closed_at":null,"days_open":91,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":91},"description":"About Hello Heart:\nHello Heart is on a mission to make heart attacks a thing of the past.\nWe’re an AI company focused exclusively on heart health, building a platform that predicts and prevents cardiac events before they happen-identifying risk up to 10 days in advance versus 10 years in traditional clinical models. \nThis is already working at scale. Hello Heart has been shown to reduce inpatient hospital days by 47% and deliver ~$1,800 in annual savings per member. Hello Heart is the cardiac prevention partner to over 80% of large U.S. health plans and serves hundreds of public and private employers.\nWe’re defining how the #1 cause of death-heart disease-is managed in the AI era. Join us.\nAbout the Role:\nHello Heart is looking for a Senior ML Engineer/ML Ops to own the engineering behind the models in the Hello Heart app: member engagement, cardiovascular risk stratification, and personalized health recommendations. You'll be the first engineer dedicated to ML on our Data Platform team, and you'll own the full model lifecycle: training pipelines, the model registry, automated evaluation and release, real-time and batch serving, monitoring, and retraining. You'll work closely with the data scientists who own the modeling and with the product engineers who call the models, so that what they build ships safely and runs reliably. Our models run on Snowflake ML. Our ML platform is still taking shape, so you'll set the standards rather than inherit them. You should have a proven record of owning ML systems in production and be comfortable using AI coding assistants as a core part of your workflow.\nResponsibilities:\n Turn model releases into a pipeline: every new version is evaluated automatically, gated against the one in production, approved, and rolled out with a fast rollback.\nBuild drift and performance monitoring for our production models, and the retraining that follows from it.\nOwn the model lifecycle end to end: training pipelines, versioning and the model registry, automated evaluation, promotion and rollback, deployment, monitoring, and retraining.\nBuild CI/CD for ML: automated testing and validation of every model version, release gates with clear criteria, and an audit trail of who shipped what and why.\nServe models in real time through our Python model-serving service and Snowflake Container Services, with a focus on low latency, reliability, and graceful degradation. Run batch inference in the warehouse with clear standards for latency, correctness, and cost.\nBuild and operate ML pipelines in Airflow and Snowflake, from feature preparation through training and batch scoring, with reproducible training data.\nMonitor drift, data quality, latency, and model performance, and automate retraining that goes through the same release gate.\nPartner with data scientists, product engineers, and data engineers. Define clear interfaces between modeling, serving, and the services that consume models, and push back when a request belongs elsewhere.\nHandle members' health data responsibly: access control, pseudonymization, and nothing sensitive in logs.\nWrite high-quality, well-tested production code, and own its observability, debugging, and reliability.\nRequirements:\n5+ years of software engineering, including 3+ years of hands-on MLOps owning production ML systems on AWS with a data or ML platform (e.g., Snowflake ML, Databricks, SageMaker, Vertex AI).\nHands-on model management: versioning, registries, automated evaluation, and promotion and rollback of models in production.\nExperience building CI/CD and pipelines for ML: automated training, validation, and deployment (e.g., Jenkins, GitHub Actions), with orchestration in Airflow or similar.\n Strong Python experience, including building and operating Python services (APIs or gateways) in production.\nExperience serving models in real time: low-latency inference, autoscaling, and reliable serving architectures.\nStrong SQL and data warehouse experience (Snowflake preferred).\nExperience monitoring models in production (drift, data quality, and performance) and acting on what you find.\nExperience owning a solution end to end, from pipeline and model integration through deployment and production debugging.\nProficiency with AI coding assistants as a core part of your workflow, and the judgment to review and verify what they produce.\nNice-to-Haves:\nSnowflake ML: Model Registry, Snowpark Container Services, ML Observability, or Notebooks and ML Jobs.\nShadow and canary releases for models.\nFeature stores and ML lifecycle tooling (e.g., Feast, MLflow, Weights & Biases).\nModel development: feature engineering, training, and evaluation with scikit-learn, XGBoost, or LightGBM.\nKubernetes and infrastructure as code (Terraform).\nEvent-driven systems (Kafka).\nIntegrating LLMs into production systems.\nObservability stacks (Prometheus, Grafana, Datadog).\nExperience with health or other regulated data (HIPAA).\nHello Heart has a positive, diverse, and supportive culture - we look for people who are collaborative, creative, and courageous. Oh, and if you want to see some recent evidence of the fun things we do at Hello Heart, check out our Instagram page.","description_format":"text","description_chars":5175,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"phd","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Care Coordination & Population Health","Consumer Health Apps"],"lifecycle":[{"event":"open","at":"2026-09-16T15:49:15Z"}],"visa":[],"liveness":{"score":20,"band":"cold","label":"Long shot","p_open":1,"p_active":0.721,"p_room":0.28,"age_days":90,"expected_fill_days":41,"reasons":["conf:1","velocity","win:tail","crowd:"],"computed_at":"2026-11-04T06:34:25Z"},"pay":null,"html_url":"https://alion.io/job/hello-heart-machine-learning-engineer-2","json_url":"https://alion.io/job/hello-heart-machine-learning-engineer-2.json","meta":{"generated_at":"2026-11-05T00:05:07Z","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":13,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-11-06T00:00:00Z"}},"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":92864},"rest":"https://alion.io/mcp/rest/get_company?id=92864"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fhello-heart-machine-learning-engineer-2"},{"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%2Fhello-heart-machine-learning-engineer-2"},{"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%2Fhello-heart-machine-learning-engineer-2"},{"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/hello-heart-machine-learning-engineer-2\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fhello-heart-machine-learning-engineer-2"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":967762}},{"tool":"search_jobs","arguments":{"company":"helloheart.com","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":967762},"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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