AI / ML Engineer

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This is a high-impact individual contributor role—ideal for someone eager to “own the outcome” and push the boundaries of “high tech + high touch” care experiences.</span><br><br></p><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><b><strong style=\"color:rgb(45,45,45);font-size:11pt;white-space:pre-wrap;\">Responsibilities</strong></b></p><ul data-pattern=\"discCircleSquare\" data-depth=\"1\" style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;margin:8px 0px;line-height:1.6;padding:0px 0px 0px 32px;list-style-type:disc;\"><li style=\"color:rgb(0,0,0);font-size:11pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Architect and build large-scale AI systems that integrate high-volume voice, text, and contextual event streams with extensive knowledge bases to deliver real-time recommendations, automations, and decision support.</span></li></ul><ul data-pattern=\"discCircleSquare\" data-depth=\"1\" style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;margin:8px 0px;line-height:1.6;padding:0px 0px 0px 32px;list-style-type:disc;\"><li style=\"color:rgb(0,0,0);font-size:11pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Design and operate workflow-oriented AI systems, including DAG-based execution graphs, stateful pipelines, and agent-driven workflows with clear observability, reproducibility, and fault tolerance.</span></li><li style=\"color:rgb(0,0,0);font-size:11pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Build agent architectures spanning agent-to-agent coordination, feedback loops, tool-calling systems, and long-running autonomous workflows, balancing control, safety, and adaptability.</span></li><li style=\"color:rgb(0,0,0);font-size:11pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Design and implement data models, feature pipelines, and APIs to support model training, low-latency inference, and continuous learning.</span></li><li style=\"color:rgb(0,0,0);font-size:11pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Develop predictive, real-time analytics systems that combine streaming data, ML inference, and event-driven triggers to surface insights and automate actions at scale.</span></li><li style=\"color:rgb(0,0,0);font-size:11pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Implement and maintain end-to-end ML platforms, including model training, evaluation, deployment, online inference, monitoring, and drift detection.</span></li><li style=\"color:rgb(0,0,0);font-size:11pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Partner closely with product managers, data scientists, and QA engineers to translate experimental models into reliable, production-grade AI services.</span></li><li style=\"color:rgb(0,0,0);font-size:11pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Identify, diagnose, and resolve performance and scaling bottlenecks across data pipelines, inference services, and orchestration layers as production workloads grow.</span></li></ul><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><br><b><strong style=\"color:rgb(45,45,45);font-size:11pt;white-space:pre-wrap;\">Required skills and qualifications</strong></b></p><ul data-pattern=\"discCircleSquare\" data-depth=\"1\" style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;margin:8px 0px;line-height:1.6;padding:0px 0px 0px 32px;list-style-type:disc;\"><li style=\"color:rgb(0,0,0);font-size:11pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">5+ years of software engineering experience, with 3+ years focused on machine learning or applied AI systems.</span></li><li style=\"color:rgb(0,0,0);font-size:11pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Strong proficiency in Python, particularly for ML pipelines, frameworks, inference services, and APIs (e.g., scikit-learn, Sanic API, PyTorch Lightning, Pydantic AI, LangGraph, Bedrock, OpenAI / Anthropic SDKs).</span></li><li style=\"color:rgb(0,0,0);font-size:11pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Experience designing ML-centric data architectures, including feature stores, vector databases, and time-series systems for monitoring and analytics.</span></li><li style=\"color:rgb(0,0,0);font-size:11pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Hands-on experience with cloud-native inference: containerized model serving, autoscaling, GPU/accelerator workloads, and low-latency production deployments.</span></li><li style=\"color:rgb(0,0,0);font-size:11pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Experience operating end-to-end MLOps platforms (e.g., MLflow, Kubeflow), including CI/CD for models, experiment tracking, and rollout strategies.</span></li><li style=\"color:rgb(0,0,0);font-size:11pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Solid understanding of workflow orchestration (graph-based execution, retries, state management) in ML and agent-based systems.</span></li><li style=\"color:rgb(0,0,0);font-size:11pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Excellent 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style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Desired skills and qualifications</strong></b></p><ul data-pattern=\"discCircleSquare\" data-depth=\"1\" style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;margin:8px 0px;line-height:1.6;padding:0px 0px 0px 32px;list-style-type:disc;\"><li style=\"color:rgb(0,0,0);font-size:11pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Experience building AI systems in healthcare or regulated environments, with familiarity with standards such as HIPAA, GDPR, or FDA guidance.</span></li><li style=\"color:rgb(0,0,0);font-size:11pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Proven experience leading complex technical initiatives and mentoring junior engineers.</span></li><li style=\"color:rgb(0,0,0);font-size:11pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Strong applied knowledge of event-driven architectures and streaming systems (Kafka, Pub/Sub, Kinesis, RabbitMQ).</span></li><li style=\"color:rgb(0,0,0);font-size:11pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Hands-on experience designing and operating vector search, RAG pipelines, and hybrid retrieval systems</span><span style=\"font-size:11pt;white-space:pre-wrap;\">.</span></li><li style=\"color:rgb(0,0,0);font-size:11pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Experience with agent frameworks, multi-agent coordination patterns, and long-running agent loops in production environments.</span><br><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Familiarity with real-time analytics stacks combining streaming data, ML inference, and operational dashboards.</span><br><br></li></ul>",
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