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Lifelancer
Lifelancer
51 – 200 Darbinieki
KonsultācijasLoģistikaVeselības aprūpe
Lifelancer ir mākslīgā intelekta darbināta talantu piesaistes platforma, kas koncentrējas uz dzīvības zinātņu, farmācijas un IT nozarēm. Tā palīdz kvalificētiem speciālistiem prezentēt savu pieredzi, atrast starptautiskas darba un projektu iespējas, kā arī sazināties ar darba devējiem, kuri meklē specializētus talantus. Personāla atlases komandām Lifelancer apvieno ar mākslīgo intelektu atbalstītu talantu meklēšanu ar atbalstu darbā pieņemšanā un algu administrēšanā vairākās valstīs, tostarp palīdzot ņemt vērā atbilstības prasības.
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Vakances uzņēmumā

Principal Machine Learning Engineer, Generative AI (Remote, US)

Lead LLM, agentic AI, and machine learning proofs of concept for Amgen’s biotech medicines business. Turn validated solutions into enterprise-ready applications.

USAmerikas Savienotās ValstisWAVašingtonaAttālinātiPilna slodzeVadošais speciālistsNepieciešamā Valoda: angļuMašīnmācīšanās inženieris
AWSMākonisPythonTerraform

Apraksts

  • Partner with business leaders to understand workflows, challenges, and goals.
  • Find AI opportunities and define what successful solutions must achieve.
  • Lead cross-functional teams in shaping unclear opportunities into focused AI initiatives.
  • Set priorities, technical direction, success measures, and adoption plans for proofs of concept.
  • Design and build AI proofs of concept using LLMs, agentic workflows, retrieval-augmented generation, data pipelines, APIs, cloud services, and enterprise platforms.
  • Take hands-on ownership of high-impact technical work.
  • Test feasibility and business value through practical experiments.
  • Plan for data readiness, integration, user experience, security, compliance, performance, cost, and operations.
  • Design scalable architectures and produce reusable components, documentation, decision records, and handoff materials.
  • Guide product and platform teams as they turn successful proofs of concept into enterprise solutions.
  • Set engineering standards through technical leadership and mentorship.
  • Shape design decisions, improve delivery practices, and help teams work through uncertainty.

Prasības

  • Doctorate plus 2 years of Machine Learning Engineer experience; master’s degree plus 6 years; bachelor’s degree plus 8 years; associate degree plus 10 years; or high school diploma or GED plus 12 years.
  • Substantial machine learning and software engineering experience, including senior technical ownership of applications taken beyond prototype or pilot stage.
  • Advanced full-stack development skills.
  • Proficiency in Python.
  • Experience building APIs, back-end applications, user interfaces, and data integrations.
  • Experience with modern software design practices.
  • Hands-on experience with cloud platforms such as AWS.
  • DevOps experience with Terraform or comparable infrastructure as code, containers, CI/CD, automated deployment, and observability.
  • Strong practical knowledge of generative AI and machine learning application design.
  • Experience selecting, evaluating, and running models, and weighing managed services, open-source tools, and custom implementations.
  • Experience with enterprise architecture and integration patterns.
  • Knowledge of access controls, sensitive-data handling, reliability, performance, and maintainability.
  • Experience developing quantitative and qualitative evaluation methods for AI applications.
  • Strong software engineering practices, including automated testing, version control, modular design, code review, documentation, and AI development tools.
  • Technical leadership demonstrated through architecture decisions, mentorship, and collaboration with business, product, engineering, security, and platform teams.
  • At least 2 years leading teams, projects, or programs, or directing resource allocation.
  • Clear written and spoken communication.
  • Experience explaining technical options and trade-offs to technical and business audiences.

Priekšrocības

  • Comprehensive employee benefits, including a retirement and savings plan with generous company contributions.
  • Group medical, dental, and vision coverage.
  • Life and disability insurance.
  • Flexible spending accounts.
  • Discretionary annual bonus program.
  • Stock-based long-term incentives.
  • Award-winning time-off plans.
  • Flexible work arrangements where possible.
  • Career development opportunities.
  • Work-life balance support.
  • Financial plans with opportunities to save for retirement and other goals.

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