Tachyon Technologies
Job Description:
We are seeking a highly skilled
AI/ML Engineer
to design, develop, and deploy scalable machine learning and artificial intelligence solutions that solve real-world business problems. The ideal candidate will have strong expertise in data science, machine learning model development, MLOps practices, and cloud-based AI services. This role involves working closely with data engineers, product teams, and software developers to build end-to-end AI/ML systems, optimize performance, and ensure seamless deployment into production environments.
Key Responsibilities:
Design, build, and optimize machine learning and deep learning models for predictive analytics, classification, recommendation systems, NLP, computer vision, and other use cases. Collaborate with data engineers to preprocess, clean, and transform structured and unstructured datasets. Implement MLOps pipelines for model training, deployment, monitoring, and version control. Optimize ML models for performance, scalability, and cost efficiency in production. Work with cloud AI/ML platforms (AWS Sagemaker, Azure ML, GCP Vertex AI) to deploy and manage models. Research and integrate the latest AI/ML frameworks, libraries, and algorithms. Partner with product and business stakeholders to translate requirements into ML solutions. Ensure models adhere to governance, compliance, and ethical AI standards. Conduct A/B testing, model evaluation, and performance monitoring to ensure accuracy and reliability. Provide technical expertise and mentorship to team members on ML best practices. Professional Skills:
Strong programming experience in Python (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch). Proficiency in SQL and experience with NoSQL databases (MongoDB, Cassandra). Hands-on experience with MLOps tools (MLflow, Kubeflow, Airflow, Docker, Kubernetes, Git). Knowledge of cloud AI services: AWS SageMaker, Azure ML Studio, GCP Vertex AI. Expertise in machine learning algorithms (regression, classification, clustering, ensemble methods). Experience with deep learning architectures (CNNs, RNNs, Transformers). Strong understanding of NLP, computer vision, and generative AI. Familiarity with big data frameworks (Spark, Hadoop) for large-scale ML training.
Skills:
Artificial Intelligence,Machine Learning
We are seeking a highly skilled
AI/ML Engineer
to design, develop, and deploy scalable machine learning and artificial intelligence solutions that solve real-world business problems. The ideal candidate will have strong expertise in data science, machine learning model development, MLOps practices, and cloud-based AI services. This role involves working closely with data engineers, product teams, and software developers to build end-to-end AI/ML systems, optimize performance, and ensure seamless deployment into production environments.
Key Responsibilities:
Design, build, and optimize machine learning and deep learning models for predictive analytics, classification, recommendation systems, NLP, computer vision, and other use cases. Collaborate with data engineers to preprocess, clean, and transform structured and unstructured datasets. Implement MLOps pipelines for model training, deployment, monitoring, and version control. Optimize ML models for performance, scalability, and cost efficiency in production. Work with cloud AI/ML platforms (AWS Sagemaker, Azure ML, GCP Vertex AI) to deploy and manage models. Research and integrate the latest AI/ML frameworks, libraries, and algorithms. Partner with product and business stakeholders to translate requirements into ML solutions. Ensure models adhere to governance, compliance, and ethical AI standards. Conduct A/B testing, model evaluation, and performance monitoring to ensure accuracy and reliability. Provide technical expertise and mentorship to team members on ML best practices. Professional Skills:
Strong programming experience in Python (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch). Proficiency in SQL and experience with NoSQL databases (MongoDB, Cassandra). Hands-on experience with MLOps tools (MLflow, Kubeflow, Airflow, Docker, Kubernetes, Git). Knowledge of cloud AI services: AWS SageMaker, Azure ML Studio, GCP Vertex AI. Expertise in machine learning algorithms (regression, classification, clustering, ensemble methods). Experience with deep learning architectures (CNNs, RNNs, Transformers). Strong understanding of NLP, computer vision, and generative AI. Familiarity with big data frameworks (Spark, Hadoop) for large-scale ML training.
Skills:
Artificial Intelligence,Machine Learning