Raas Infotek LLC
Job Title: Senior AI/ML Engineer
Location: Charlotte, NC (Hybrid)
Employment Type: W2 Only (NO C2C/1099)
Duration: 12 Months
About the Role
We are seeking a highly skilled
Senior AI/ML Engineer
to lead the design, development, and deployment of advanced machine learning and artificial intelligence solutions. This role is ideal for someone who thrives in a fast-paced, data-driven environment and is passionate about solving complex problems using cutting-edge AI/ML technologies. Key Responsibilities
Design, develop, and deploy
machine learning models ,
deep learning architectures , and
AI-driven applications . Collaborate with data scientists, data engineers, and product teams to translate business requirements into scalable ML solutions. Build and optimize
end-to-end ML pipelines
for data ingestion, feature engineering, model training, evaluation, and deployment. Leverage cloud platforms such as
AWS ,
Azure , or
Google Cloud Platform
for scalable model training and deployment. Apply
MLOps best practices
to automate model versioning, testing, monitoring, and retraining. Conduct
exploratory data analysis (EDA)
and use statistical techniques to extract insights from large datasets. Work with
structured and unstructured data , including text, images, and time-series data. Stay current with the latest research and trends in AI/ML and apply them to real-world problems. Mentor junior engineers and contribute to the development of internal AI/ML frameworks and tools. Required Skills & Qualifications
10 years
of experience in
machine learning ,
data science , or
AI engineering
roles. Strong programming skills in
Python
and experience with libraries such as
TensorFlow ,
PyTorch ,
scikit-learn ,
XGBoost , and
Pandas . Experience with
deep learning ,
NLP ,
computer vision , or
time-series forecasting . Proficiency in
SQL
and working with large-scale datasets. Hands-on experience with
cloud platforms
(AWS/Google Cloud Platform/Azure) and
ML services
(e.g., SageMaker, Vertex AI, Azure ML). Familiarity with
MLOps tools
such as
MLflow ,
Kubeflow ,
Airflow , or
DVC . Strong understanding of
data structures ,
algorithms , and
software engineering principles . Excellent problem-solving, communication, and collaboration skills. Nice to Have
Experience with
generative AI ,
LLMs , or
foundation models . Knowledge of
big data technologies
(e.g., Spark, Hadoop, Kafka). Exposure to
data labeling ,
model explainability , and
bias mitigation
techniques. Experience with
containerization
and
orchestration tools
like
Docker
and
Kubernetes . Publications or contributions to open-source AI/ML projects. Certifications (Preferred)
Google Professional Machine Learning Engineer AWS Certified Machine Learning Specialty Microsoft Certified: Azure AI Engineer Associate
#J-18808-Ljbffr
We are seeking a highly skilled
Senior AI/ML Engineer
to lead the design, development, and deployment of advanced machine learning and artificial intelligence solutions. This role is ideal for someone who thrives in a fast-paced, data-driven environment and is passionate about solving complex problems using cutting-edge AI/ML technologies. Key Responsibilities
Design, develop, and deploy
machine learning models ,
deep learning architectures , and
AI-driven applications . Collaborate with data scientists, data engineers, and product teams to translate business requirements into scalable ML solutions. Build and optimize
end-to-end ML pipelines
for data ingestion, feature engineering, model training, evaluation, and deployment. Leverage cloud platforms such as
AWS ,
Azure , or
Google Cloud Platform
for scalable model training and deployment. Apply
MLOps best practices
to automate model versioning, testing, monitoring, and retraining. Conduct
exploratory data analysis (EDA)
and use statistical techniques to extract insights from large datasets. Work with
structured and unstructured data , including text, images, and time-series data. Stay current with the latest research and trends in AI/ML and apply them to real-world problems. Mentor junior engineers and contribute to the development of internal AI/ML frameworks and tools. Required Skills & Qualifications
10 years
of experience in
machine learning ,
data science , or
AI engineering
roles. Strong programming skills in
Python
and experience with libraries such as
TensorFlow ,
PyTorch ,
scikit-learn ,
XGBoost , and
Pandas . Experience with
deep learning ,
NLP ,
computer vision , or
time-series forecasting . Proficiency in
SQL
and working with large-scale datasets. Hands-on experience with
cloud platforms
(AWS/Google Cloud Platform/Azure) and
ML services
(e.g., SageMaker, Vertex AI, Azure ML). Familiarity with
MLOps tools
such as
MLflow ,
Kubeflow ,
Airflow , or
DVC . Strong understanding of
data structures ,
algorithms , and
software engineering principles . Excellent problem-solving, communication, and collaboration skills. Nice to Have
Experience with
generative AI ,
LLMs , or
foundation models . Knowledge of
big data technologies
(e.g., Spark, Hadoop, Kafka). Exposure to
data labeling ,
model explainability , and
bias mitigation
techniques. Experience with
containerization
and
orchestration tools
like
Docker
and
Kubernetes . Publications or contributions to open-source AI/ML projects. Certifications (Preferred)
Google Professional Machine Learning Engineer AWS Certified Machine Learning Specialty Microsoft Certified: Azure AI Engineer Associate
#J-18808-Ljbffr