Job Description

Job Title: Python Developer with AI/ML Experience - W2 Only - We can provide sponsorship

Duration: Long Term

Location: Jersey City, NJ - Hybrid

What are the top three MUST have skills

• -Python software development
• -Packaging and containerizing using CI/CD technology (jenkins docker terraform etc)
• -Experience building (Rest, Flask, or FastAPI) APIs

What are the NICE to have skills:

-Cloud experience (AWS, sagemaker, bedrock, lambda, cloudformation)

-Azure cognitive services

-General AI/ML tools experience with (triton inference server, deep java library, huggingface)

-Postgres or DynamoDB

The Expertise You Have

• Has Bachelor’s or Master’s Degree or equivalent experience in a technology related field (e.g. Computer Science, Engineering, etc.).
• Proficiency in Python software development with strong experience in its ML ecosystem (numpy, pandas, sklearn, tensorflow, etc.), along with solid skills in Linux scripting. Ability to design and implement software using both object-oriented and functional programming paradigms. Basic knowledge of Java and Groovy is a plus.
• Proven experience in building cloud-native applications using a range of AWS services, including but not limited to SageMaker AI, Bedrock, S3, CloudFormation (CFT), SNS, SQS, Lambda, AWS Batch, Step Functions, EventBridge, and CloudWatch. Familiarity with both Azure Cognitive Services, particularly for deploying OpenAI models, and Google Compute Vertex is beneficial.
• Strong experience with CI/CD tools, particularly Jenkins, for automating and streamlining the software development pipeline. Proficient in using version control systems like Git for effective code management and collaboration. Hands-on experience with containerization technologies such as Docker for building and deploying applications. Expertise in infrastructure as code (IaC) services, including AWS CloudFormation and tools like Terraform or OpenTofu, for managing and provisioning cloud resources
• Extensive experience working with machine learning models with respect to deployment, inference, tuning, and measurement required.
• Strong knowledge of developing highly scalable distributed systems using Open-source technologies.
• 5+ years of proven experience in developing and implementing Python-based cloud applications and/or machine learning solutions.
• Solid experience in Agile methodologies (Kanban and SCRUM).

The Skills You Bring

• You have strong technical design and analysis skills.
• You the ability to deal with ambiguity and work in fast paced environment.
• Your experience supporting critical applications.
• You are familiar with applied data science methods, feature engineering and machine learning algorithms.
• Your Data wrangling experience with structured, semi-structure and unstructured data.
• Your experience building ML infrastructure, with a strong focus on software engineering.
• You have excellent communication skills, both through written and verbal channels.
• You have excellent collaboration skills to work with multiple teams in the organization.
• Your ability to understand and adapt to changing business priorities and technology advancements in a Data Science and Big data ecosystem.

The Value You Deliver

• Partner with Data Scientists and to help use the foundational platform upon which models can be built and trained.
• Operationalize ML Models at scale (e.g. Serve predictions on tens of millions of customers).
• Exploring new technology trends and maximizing them to simplify our data and ML ecosystem.
• Designing & developing a feature generation & store framework that promotes sharing of data/features among different ML models.
• Build tools to help detect shifts in data/features used by ML models to help identify issues in advance of deteriorating prediction quality, monitoring the uncertainty of model outputs, automating prediction explanation for model diagnostics.
• Driving Innovation and implementing solutions with future thinking.
• Guiding teams to improve development agility and productivity.
• Resolving technical roadblocks and mitigating potential risks.
• Delivering system automation

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