SoftStandard SolutionsRemote
Machine Learning Engineer
United States of America
Full Time
1 day ago
H1B Sponsor Likely
Key skills
PythonObject-oriented programmingData structuresAlgorithmsFastAPIFlaskDjangoScikit-learnTensorFlowPyTorchSupervised learningUnsupervised learningFeature engineeringModel evaluationHyperparameter tuningModel optimizationGenerative AILarge Language Models (LLMs)Retrieval-Augmented Generation (RAG)Prompt engineeringEmbeddingsFAISSPineconeChromaDBData pipelinesSQLPostgreSQLMySQLSQL ServerMongoDBAWSMicrosoft AzureGoogle Cloud PlatformDockerKubernetesGitCI/CD pipelinesAWS Certified Machine Learning Engineer – AssociateMicrosoft Certified Azure AI Engineer Associate (AI-102)Google Professional Machine Learning EngineerPCAP – Certified Associate in Python ProgrammingNoSQLAIArtificial IntelligenceMachine LearningMLNLPComputer VisionLarge Language ModelsRAGscikit-learnMLOpsMLflowKubeflowAnalyticsAirflowAzureGoogle CloudRESTfulAgileCI/CDCommunicationCollaboration
About this role
SoftStandard Solutions is seeking a passionate AI/ML Engineer with strong Python development experience. The role involves building scalable AI solutions, developing production-ready Python applications, and working with modern Machine Learning and Generative AI technologies.
Responsibilities:
- We're looking for a passionate AI/ML Engineer with strong Python development experience to join our growing team
- If you enjoy building scalable AI solutions, developing production-ready Python applications, and working with modern Machine Learning and Generative AI technologies, we'd love to hear from you
Requirements:
- 4–6 years of hands-on experience in Python development, Machine Learning, and AI application development
- Strong proficiency in Python with solid knowledge of object-oriented programming, data structures, algorithms, and software development best practices
- Experience building scalable backend applications and RESTful APIs using FastAPI, Flask, or Django
- Hands-on experience designing, training, evaluating, and deploying Machine Learning models using Scikit-learn, TensorFlow, or PyTorch
- Strong understanding of supervised and unsupervised learning, feature engineering, model evaluation, hyperparameter tuning, and model optimization techniques
- Experience with Generative AI, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), prompt engineering, embeddings, and vector databases such as FAISS, Pinecone, or ChromaDB
- Experience building end-to-end data pipelines for data ingestion, preprocessing, feature engineering, model deployment, and monitoring
- Strong knowledge of SQL and experience working with relational and NoSQL databases such as PostgreSQL, MySQL, SQL Server, or MongoDB
- Experience with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform, along with Docker, Kubernetes, Git, and CI/CD pipelines
- Excellent analytical, problem-solving, communication, and collaboration skills with the ability to work in an Agile environment
- Bachelor's or Master's degree in Computer Science, Information Technology, Artificial Intelligence, Data Science, or a related field
- Familiarity with MLOps tools such as MLflow, Airflow, or Kubeflow is a plus
- Exposure to NLP, Computer Vision, Recommendation Systems, or Predictive Analytics is preferred
- AWS Certified Machine Learning Engineer – Associate
- Microsoft Certified: Azure AI Engineer Associate (AI-102)
- Google Professional Machine Learning Engineer
- PCAP – Certified Associate in Python Programming (Python Institute)