Development Engineer/LEAD MACHINE LEARNING ENGINEER

Job Description

Job DescriptionLocal candidates onlyMust have local project in recent/Local DL copyOverall 7+ years of expVisa - OPT/CPT/H4 EAD/Gc EAD/L2 EAD/USC/GC onlyRate - $65-70/hr W2 + $7 referral, open for higher rate based on their exp.Client - TARGETLocation - Minneapolis, MN - Hybrid 2 days onsiteRole - Development Engineer/LEAD MACHINE LEARNING ENGINEERDuration - 6-12 months contract with long term extensionMust Have:KaftkaMachine LearningMachine Learning DevelopmentPython, Pyspark or ScalaSPARKNice to Have:JavaAS A LEAD MACHINE LEARNING ENGINEERAbout Us:Join our global in-house Tech and Data Sciences teamAs Lead Machine Learning Engineer, you will join a Data Sciences team responsible for creating personalized recommendations on Target.com and the Target App. You will play a crucial role in designing, implementing, and optimizing production machine learning solutions. We will also expect you to understand best practice software design, participate in code reviews, and create a maintainable well-tested codebase with relevant documentation. At an organizational level, you will conduct training sessions, present work to technical and non-technical peers/leaders, build knowledge on business priorities/strategic goals and leverage this knowledge while building requirements and solutions for each business need.Core responsibilities of this job are articulated within this job description. Job duties may change at any time due to business needs.Qualifications:

• 4-year degree in Quantitative disciplines (Science, Technology, Engineering, Mathematics) or equivalent experience
• MS in Computer Science, Applied Mathematics, Statistics, Physics or equivalent work or industry experience
• 5 plus years' experience in end-to-end Machine Learning application development, including data pipelining, model optimization, deployment, and API design
• Highly proficient programming in Python and either PySpark or Scala
• Experience with ML frameworks such as Pytorch, TensorFlow, xgboost, sklearn, and ONNX
• Experience with one or more cloud ML services such as Vertex AI/Azure ML/Sagemaker
• Experience using distributed training frameworks like Spark/Ray/TensorFlow Distribute
• Experience with serving frameworks such as TorchServe/TensorFlow Serving/FastAPI
• Good understanding of Big Data tech, specifically Kafka, Spark
• Experience creating and maintaining CI/CD pipelines for automated model deployment and testing
• Work in partnership with data scientists, software engineers and product managers to understand the business requirements and translate to machine learning solutions at scale
• Excellent communication skills with the ability to clearly tell data driven stories through appropriate visualizations, graphs, and narratives
• Self-driven and results oriented; able to meet tight timelines
• Ability to collaborate effectively across global team
• Experience in mentoring the junior team members ML skillset and career development

Nice to Have:

• PhD in Computer Science, Applied Mathematics, Statistics, Physics or related quantitative field
• Proficiency in Java
• This position will operate as a Hybrid/Flex for Your Day work arrangement based on ***'s needs. A Hybrid/Flex for Your Day work arrangement means the team member's core role will need to be performed both onsite at the *** HQ location the role is assigned to and virtually, depending upon what your role, team and tasks require for that day. Work duties cannot be performed outside of the country of the primary work location, unless otherwise prescribed by ***.
• Onsite 1 day a week at minimum. Sometimes teams may require up to 3 days and full Core Weeks attendance.

UrBench is an equal opportunity employer and is committed to creating a diverse environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, pregnancy, status as a parent, disability, age, veteran status, or other characteristics as defined by federal, state or local laws.