Hexanixone is hiring: Machine Learning Engineer in San Francisco
Hexanixone, San Francisco, CA, United States
AI & ML Ahmedabad / Remote Full-time as per the market standards
About the Role Join our AI/ML team to build and deploy state-of-the-art machine learning systems for enterprise clients. You'll work on diverse projects ranging from LLM fine-tuning to computer vision applications, collaborating with cross-functional teams to deliver impactful AI solutions at scale.
Key Responsibilities Design and implement ML models for various use cases
Fine-tune and deploy LLMs for enterprise applications
Build MLOps pipelines for model training and deployment
Optimize model performance and reduce inference latency
Collaborate with product teams to translate requirements into ML solutions
Monitor model performance and implement retraining strategies
Research and evaluate new ML techniques and frameworks
Contribute to ML infrastructure and tooling development
Required Qualifications 4+ years of ML engineering experience
Strong Python skills and ML frameworks (TensorFlow, PyTorch)
Experience with LLMs (GPT-4, Claude, Llama) and fine-tuning
Knowledge of MLOps tools and practices
Solid understanding of statistics and ML algorithms
Experience deploying models to production at scale
Strong software engineering fundamentals
MS or BS in Computer Science, ML, or related field
Nice to Have PhD in Computer Science, ML, or related field
Experience with AWS SageMaker or Azure ML
Published research or contributions to ML frameworks
Experience with computer vision or NLP
Knowledge of distributed training and optimization
Background in deep learning and neural architecture search
What We Offer Competitive compensation package
Hybrid work model with flexible hours
Microsoft certifications fully sponsored
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About the Role Join our AI/ML team to build and deploy state-of-the-art machine learning systems for enterprise clients. You'll work on diverse projects ranging from LLM fine-tuning to computer vision applications, collaborating with cross-functional teams to deliver impactful AI solutions at scale.
Key Responsibilities Design and implement ML models for various use cases
Fine-tune and deploy LLMs for enterprise applications
Build MLOps pipelines for model training and deployment
Optimize model performance and reduce inference latency
Collaborate with product teams to translate requirements into ML solutions
Monitor model performance and implement retraining strategies
Research and evaluate new ML techniques and frameworks
Contribute to ML infrastructure and tooling development
Required Qualifications 4+ years of ML engineering experience
Strong Python skills and ML frameworks (TensorFlow, PyTorch)
Experience with LLMs (GPT-4, Claude, Llama) and fine-tuning
Knowledge of MLOps tools and practices
Solid understanding of statistics and ML algorithms
Experience deploying models to production at scale
Strong software engineering fundamentals
MS or BS in Computer Science, ML, or related field
Nice to Have PhD in Computer Science, ML, or related field
Experience with AWS SageMaker or Azure ML
Published research or contributions to ML frameworks
Experience with computer vision or NLP
Knowledge of distributed training and optimization
Background in deep learning and neural architecture search
What We Offer Competitive compensation package
Hybrid work model with flexible hours
Microsoft certifications fully sponsored
#J-18808-Ljbffr