Machine Learning Engineer

2 months ago

Minnesota, United States Securian Financial Group Full time
Job Title: Machine Learning Engineer

At Securian Financial, we're seeking a highly skilled Machine Learning Engineer to join our team. As a key member of our data science team, you'll be responsible for designing, developing, and deploying machine learning models to solve complex business problems.

Key Responsibilities:
  • Lead the design and development of machine learning pipelines for advanced AI algorithms and models.
  • Collaborate with research scientists, data scientists, and software engineers to translate research findings into practical AI solutions.
  • Evaluate and experiment with emerging AI technologies, frameworks, and methodologies to stay at the forefront of innovation.
  • Provide technical guidance and mentorship to junior team members, fostering a culture of continuous learning and growth.
  • Deploy, test, and optimize machine learning models and data pipelines in production environments.
Requirements:
  • Advanced degree (Master's or Ph.D.) or equivalent industry experience in Computer Science, Machine Learning, or related fields.
  • 5+ years of experience in a similar role in a production environment.
  • Experience working with large-scale datasets and building ETL pipelines using Spark, Kubeflow, StreamSets, etc.
  • Hands-on experience with cloud computing platforms such as AWS.
  • Strong proficiency in Python and experience with NLP techniques, resources, and methodologies such as Scikit-learn, TensorFlow, PyTorch, HuggingFace, Comprehend, XGBoost, LangChain, etc.
What We Offer:
  • A comprehensive range of benefits designed to enhance your professional growth, well-being, and work-life balance.
  • A hybrid work arrangement that allows for flexibility and work-life balance.
  • Opportunities for professional growth and development.

We're an equal employment opportunity employer and welcome applications from diverse candidates. If you're a job seeker with a disability and require an accommodation to apply for this job, please contact us by email at [email address] or by telephone at [phone number] (voice) or 711 (Relay/TTY).

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