AI/ML Engineering Manager

Stelle nicht auf LinkedIn

🔥 vor 5 Stunden

🇺🇸 Vereinigte Staaten – Remote

💵 $140.000 - $215.000 / Jahr

⏰ Vollzeit

🟠 Senior

🔴 Experte

👮‍♀️ Leiter Softwareentwicklung

👻 Geisterscore 0%

Was es bedeutet: die Wahrscheinlichkeit, dass für diese Stelle niemand wirklich einstellt.So liest du es: 60 % oder höher heißt, wir halten das für einen Geisterjob. Niedrigere Werte sind weniger bedenklich.Wie wir werten: Dauer offen, Neuveröffentlichungen, offene Stellen vs Teamgröße, wie schnell Stellen geschlossen werden, und ob ein Gehalt angegeben ist.Hinweis: eine Schätzung aus öffentlichen Daten, kein Urteil über das Unternehmen. Echte Stellen können hoch punkten, nutze es also als Hinweis, nicht als Fakt.

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Caylent

WebsiteLinkedInAlle Stellen

201 - 500 Mitarbeiter

💼 Beratung

📦 Logistik

📣 Marketing

💰 Private Equity Round im 2022-11

Consulting • Logistics • Marketing

Caylent ist ein Cloud-Native-Serviceunternehmen, das Organisationen dabei unterstützt, mit AWS das Beste aus ihren Mitarbeitenden und ihrer Technologie herauszuholen. Als führender AWS Consulting Partner ist Caylent auf DevOps-as-a-Service, IaaS, DevOps, SaaS und verschiedene Cloud-Technologien spezialisiert, darunter Amazon Web Services und Google Cloud Platform. Das Unternehmen stärkt Organisationen durch Technologie, damit sie in einer softwaredefinierten Welt erfolgreich sind und Innovationen vorantreiben können.

Beschreibung

• Report to the Director of AI/ML • Hire and build a team of ML engineers and architects • Set technical standards, oversee technical assessments, and make hiring decisions • Conduct structured 1:1s, provide feedback, and support team members’ career growth • Manage performance, recognize strong contributors, and address performance gaps • Partner with HRBPs and the Director of AI/ML on structured performance situations • Monitor staffing and align team members with appropriate engagement opportunities • Lead end-to-end ML assessments covering infrastructure, data pipelines, model lifecycle, and organizational readiness • Produce recommendations that support executive decisions and future engagements • Serve as senior technical authority on customer engagements and shape architecture • Advise customers on MLOps, LLMOps, production monitoring, and sustainable ML systems • Partner with sales and solutions teams on scoping and proposals • Lead architecture and solution design from kickoff through delivery • Unblock teams on complex technical problems and ensure Caylent quality standards • Own architect-level client relationships and technical outcomes • Mentor engineers and architects, contribute to technical interviews, and create reference architectures and reusable ML accelerators • Help grow the broader ML practice

🎯 Anforderungen

• 10+ years in machine learning or AI, with a proven track record of leading client-facing engagements in a consulting or advisory capacity • Demonstrated people management experience, including hiring, performance calibration, career development, and difficult conversations • Deep, current knowledge of the AWS ML and GenAI ecosystem • Ability to make and defend architectural decisions across the full ML lifecycle, from data and feature engineering through training, deployment, and monitoring • Deep expertise in at least two or three ML domains, such as classical ML, computer vision, NLP, or time series • Proven ability to architect and govern production ML systems end-to-end • Experience translating MLOps, LLMOps, and AI operations complexity into executable engineering standards and actionable executive guidance • Deep expertise in foundation model adaptation, including fine-tuning (LoRA, QLoRA, PEFT), alignment (RLHF, DPO), inference optimization, and distributed training • Experience with RAG and agentic system design, including multi-agent architectures, MCP integration, and human-in-the-loop patterns on AWS • Ability to operate independently in complex, ambiguous customer environments and translate ML tradeoffs into business risk and value • Current legal authorization to work in the country where the position is located; Caylent cannot sponsor visa or work permit applications • AWS Certified Machine Learning – Specialty and/or AWS Certified Solutions Architect – Professional are strong differentiators, not required • Technical stack knowledge spanning AWS SageMaker, Bedrock, Anthropic API, OpenAI API, Google Gemini API, Azure OpenAI, AWS AI services, Spark/PySpark, Kafka, Kinesis, vector databases, PyTorch, TensorFlow, JAX, Scikit-learn, XGBoost, HuggingFace, LangChain, LlamaIndex, MLflow, Airflow/MWAA, Dagster, Kubeflow, CI/CD, IaC, Docker, Kubernetes, ML governance, responsible AI, LLM evaluation and safety, and inference optimization tools

🏖️ Vorteile

• Medical Insurance for you and eligible dependents • 401k plan with company match up to 4% and immediate vesting • Competitive phantom equity • Company issued laptop • Dental and Vision insurance • Term Disability Insurance • Term Life Insurance • Flexible Spending Account • Equipment & Office Stipend • Annual stipend for Learning and Development • Unlimited Paid Time Off, following a 90-day probationary period • 10 Paid Holidays

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