AI Application Architect

OpenKyber LLC

4 days ago

Role details

Contract type

Temporary to permanent

Employment type

Full-time (> 32 hours)

Working hours

Regular working hours

Languages

English

Experience level

Intermediate

Job location

Tech stack

Java

Artificial Intelligence

Amazon Web Services (AWS)

Data analysis

Artificial Neural Networks

Azure

Big Data

Computer Programming

Data Cleansing

Data Transformation

Database Applications

Python

Machine Learning

NLTK

NoSQL

TensorFlow

SQL Databases

Management of Software Versions

Reinforcement Learning

Google Cloud Platform

Cloud Platform System

Feature Engineering

PyTorch

Spark

Keras

AI Platforms

Scikit Learn

HuggingFace

Data Management

Machine Learning Operations

Spacy

Data Pipelines

Job description

We are seeking a Mid-Level AI Platform Developer to support the design, development, and deployment of advanced AI/ML solutions. This individual will play a key role in building scalable AI platforms, collaborating with cross-functional teams, and delivering high-quality machine learning models and data-driven applications. The ideal candidate will have a strong technical foundation in programming, machine learning, and cloud-based deployment., * Design, develop, and deploy machine learning and deep learning models

Build and maintain scalable AI platforms and data pipelines
Perform data acquisition, preprocessing, and feature engineering
Collaborate with cross-functional teams including engineering, operations, and business stakeholders
Optimize and monitor model performance in production environments
Support MLOps processes including model deployment, versioning, and lifecycle management
Work with large datasets using big data technologies

Requirements

5 7 years of experience in AI/ML development or related field
Strong programming skills in Python (required); experience with R, Java, or C is a plus
Deep understanding of machine learning concepts (supervised, unsupervised, reinforcement learning)
Experience with neural networks including CNNs and RNNs
Hands-on experience with AI/ML frameworks such as TensorFlow, PyTorch, Keras, and scikit-learn
Strong data analysis skills including data cleaning, preprocessing, and feature engineering
Experience with SQL and/or NoSQL databases
Familiarity with big data tools such as Apache Spark and OpenSearch
Solid foundation in mathematics and statistics (linear algebra, calculus, probability), * Experience with Natural Language Processing (NLP) tools such as NLTK, spaCy, or Hugging Face Transformers
Experience working in cloud environments (AWS, Azure, or Google Cloud Platform)
Knowledge of MLOps principles and tools for model deployment and monitoring