EnIn Systems
Senior Machine Learning Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior Machine Learning Engineer on a contract W2 basis, requiring 10+ years of experience. Key skills include Python, TensorFlow, and NLP. The position is onsite, focusing on AI/ML solutions in Healthcare, FinTech, or E-commerce.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
February 19, 2026
🕒 - Duration
Unknown
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🏝️ - Location
On-site
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📄 - Contract
W2 Contractor
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🔒 - Security
Unknown
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📍 - Location detailed
New Jersey, United States
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🧠 - Skills detailed
#NumPy #Pandas #Scala #ML (Machine Learning) #MLflow #REST (Representational State Transfer) #Deep Learning #Model Deployment #Azure #Data Engineering #Classification #NoSQL #S3 (Amazon Simple Storage Service) #NLP (Natural Language Processing) #BERT #Clustering #Python #Libraries #EC2 #AWS SageMaker #SageMaker #R #Cloud #TensorFlow #Airflow #Programming #Keras #Kubernetes #Transformers #Deployment #Data Ingestion #OpenCV (Open Source Computer Vision Library) #AI (Artificial Intelligence) #"ETL (Extract #Transform #Load)" #Spark (Apache Spark) #AWS (Amazon Web Services) #Docker #FastAPI #Hadoop #PyTorch #REST API #Regression #GCP (Google Cloud Platform) #Langchain #Neural Networks #SQL (Structured Query Language) #Monitoring #Big Data #Databricks #Flask
Role description
Job Title: Senior AI / Machine Learning Engineer
Experience: 10+ Years
Location: Onsite
Employment Type: Contract W2
Job Summary
We are seeking a highly experienced Senior AI & Machine Learning Engineer with 10+ years of experience in designing, building, and deploying scalable AI/ML solutions. The ideal candidate will lead end-to-end machine learning projects, mentor junior engineers, and work closely with business stakeholders to deliver data-driven solutions.
Key Responsibilities
Design, develop, and deploy Machine Learning and Deep Learning models in production.
Build end-to-end ML pipelines including data ingestion, preprocessing, training, validation, and deployment.
Work on Generative AI models (LLMs, RAG, chatbots, embeddings, prompt engineering).
Implement models using TensorFlow, PyTorch, Scikit-learn.
Apply NLP, Computer Vision, and Predictive Analytics techniques.
Optimize model performance, scalability, and reliability.
Collaborate with Data Engineers, Product Managers, and Business teams.
Mentor junior ML engineers and review code.
Ensure best practices for MLOps, CI/CD, and model monitoring.
Required Skills
Core AI/ML:
Strong experience in Machine Learning, Deep Learning, Statistical Modeling
Algorithms: Regression, Classification, Clustering, XGBoost, Random Forest, Neural Networks
NLP: Transformers, BERT, GPT, LLMs
Computer Vision: CNN, OpenCV
Programming:
Python (must), R/Scala (good to have)
Libraries: NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, Keras
Data & Big Data:
SQL, NoSQL
Spark, Hadoop, Databricks
Data preprocessing and feature engineering
MLOps & Deployment:
Model deployment using Docker, Kubernetes, MLflow, Airflow
REST APIs using FastAPI/Flask
CI/CD pipelines for ML
Cloud Platforms:
AWS (SageMaker, EC2, S3)
Azure (Azure ML, Cognitive Services)
GCP (Vertex AI)
Nice to Have
Experience with Generative AI tools (LangChain, LlamaIndex, OpenAI APIs)
Knowledge of LLM fine-tuning, RAG, Vector DBs (Pinecone, FAISS, Weaviate)
Experience in Healthcare/FinTech/E-commerce domains
Publications or patents in AI/ML
Job Title: Senior AI / Machine Learning Engineer
Experience: 10+ Years
Location: Onsite
Employment Type: Contract W2
Job Summary
We are seeking a highly experienced Senior AI & Machine Learning Engineer with 10+ years of experience in designing, building, and deploying scalable AI/ML solutions. The ideal candidate will lead end-to-end machine learning projects, mentor junior engineers, and work closely with business stakeholders to deliver data-driven solutions.
Key Responsibilities
Design, develop, and deploy Machine Learning and Deep Learning models in production.
Build end-to-end ML pipelines including data ingestion, preprocessing, training, validation, and deployment.
Work on Generative AI models (LLMs, RAG, chatbots, embeddings, prompt engineering).
Implement models using TensorFlow, PyTorch, Scikit-learn.
Apply NLP, Computer Vision, and Predictive Analytics techniques.
Optimize model performance, scalability, and reliability.
Collaborate with Data Engineers, Product Managers, and Business teams.
Mentor junior ML engineers and review code.
Ensure best practices for MLOps, CI/CD, and model monitoring.
Required Skills
Core AI/ML:
Strong experience in Machine Learning, Deep Learning, Statistical Modeling
Algorithms: Regression, Classification, Clustering, XGBoost, Random Forest, Neural Networks
NLP: Transformers, BERT, GPT, LLMs
Computer Vision: CNN, OpenCV
Programming:
Python (must), R/Scala (good to have)
Libraries: NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, Keras
Data & Big Data:
SQL, NoSQL
Spark, Hadoop, Databricks
Data preprocessing and feature engineering
MLOps & Deployment:
Model deployment using Docker, Kubernetes, MLflow, Airflow
REST APIs using FastAPI/Flask
CI/CD pipelines for ML
Cloud Platforms:
AWS (SageMaker, EC2, S3)
Azure (Azure ML, Cognitive Services)
GCP (Vertex AI)
Nice to Have
Experience with Generative AI tools (LangChain, LlamaIndex, OpenAI APIs)
Knowledge of LLM fine-tuning, RAG, Vector DBs (Pinecone, FAISS, Weaviate)
Experience in Healthcare/FinTech/E-commerce domains
Publications or patents in AI/ML
