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Machine Learning Engineer
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Smart IT Frame LLC
Dallas, TX (In Person)
Full-Time
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Job Description
Machine Learning Engineer at Smart IT Frame LLC Machine Learning Engineer at Smart IT Frame LLC in Dallas, Texas Posted in about 21 hours ago.
Strong programming expertise i n Python, with hands-on experience in Pandas, PySpark, and PyArro w.
Deep understanding of th e Hadoop ecosystem, distributed computing, and performance tunin g.
Experience wit h CI/CD pipelines and best practices in ML environmen t s.
Hands-on experience with monitoring tools fo r ML pipeline health and performanc e.
Strong collaboration skills wit h experience working in cross-functional teams (platform, data science, engineering ).Experience contributing to or building interna l MLO ps frameworks/platform s.
Familiarity wit h SLU RM clusters or other distributed job scheduler s.
Exposur e to Kafka, Spark Streaming, or other real-time data processing technologie s.
Understanding o f ML lifecycle management, including versioning, deployment, and drift detectio n.
Type:
full-timeJob Description:
Job Role:
Machine Learning Operations Engineer Location:
Dallas, TX or Pittsburgh PA (Onsite)Mode of Hiring:
Contract /FTE Mandatory Skills :
Apache Kafk aHadoop Hiv ePanda sPytho n Required Qualification s:6+ years of experience in software engineering, data engineering, or MLOps role s.Strong programming expertise i n Python, with hands-on experience in Pandas, PySpark, and PyArro w.
Deep understanding of th e Hadoop ecosystem, distributed computing, and performance tunin g.
Experience wit h CI/CD pipelines and best practices in ML environmen t s.
Hands-on experience with monitoring tools fo r ML pipeline health and performanc e.
Strong collaboration skills wit h experience working in cross-functional teams (platform, data science, engineering ).Experience contributing to or building interna l MLO ps frameworks/platform s.
Familiarity wit h SLU RM clusters or other distributed job scheduler s.
Exposur e to Kafka, Spark Streaming, or other real-time data processing technologie s.
Understanding o f ML lifecycle management, including versioning, deployment, and drift detectio n.