Develop and deploy ML models and pipelines. Utilize AWS services, including SageMaker, Bedrock, Lambda, StepFunctions, and S3. Collaborate with remote teams to deliver scalable technical solutions.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Nice to Have
Job Description
ML Engineer - 100% Remote
Location - 100% Remote
Job Type - Contract
Budget - 1.2 LPM
Experience - 5+ Years
Required Qualifications
* Technical Expertise:
o 5+ years of professional experience in developing and deploying ML models and
pipelines.
o Proven expertise in AWS services including SageMaker, Bedrock, Lambda, Step
Functions, and S3.
o Strong proficiency in Python and/or PySpark for data manipulation, model
development, and pipeline implementation.
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GitLab or similar version control systems.
o Practical experience in building solutions for entity matching, fraud detection, and
transaction matching within a master data management context.
o Familiarity with generative AI models and their application within data
processing workflows.
* Analytical & Problem-Solving Skills:
o Ability to transform complex business requirements into scalable technical
solutions.
o Strong data analysis capabilities with a track record of developing models that
provide actionable insights.
* Communication & Collaboration:
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o Excellent verbal and written communication skills.
o Demonstrated ability to work independently as a contractor while effectively
collaborating with remote teams.
o Proven record of quickly adapting to new technologies and agile work
environments.
Preferred Qualifications
* Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a
related field.
* Experience with additional AWS services such as Kinesis, Firehose, and SQS.
* Prior experience in a consulting or contracting role, demonstrating the ability to manage
deliverables under tight deadlines.
* Experience within industries where data security and compliance are critical
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