Insight Global
Insight Global is seeking a team of experienced, driven Machine Learning Engineer to join an established health technology company sitting remotely in the PST or CST time zone. This is a full-time, permanent role with competitive salary, bonus, and comprehensive benefits.
In this role you'll need: Deep Learning Frameworks: Hands-on experience with PyTorch (main focus) and familiarity with TensorFlow.
Large-Scale Model Training: Exposure to advanced training techniques like Distributed Data Parallel (DDP), Fully Sharded Data Parallel (FSDP), ZeRO, and model parallelism (pipeline/tensor). Experience with distributed training is a strong plus.
Model Optimization: Skilled in improving model performance through techniques like quantization (PTQ, QAT, AWQ, GPTQ), pruning, knowledge distillation, KV-cache tuning, and using efficient attention mechanisms like Flash Attention.
Scalable Model Serving: Understanding of how to deploy models at scale, including autoscaling, load balancing, streaming, batching, and caching. Comfortable working alongside platform engineers to build robust serving pipelines.
Data & Storage Systems: Proficient with both SQL and NoSQL databases, vector databases (e.g., FAISS, Milvus, Pinecone, pgvector), and data formats like Parquet and Delta. Familiar with object storage systems.
Code Quality: Writes efficient, clean, and maintainable code with a focus on performance.
End-to-End ML Lifecycle: Solid grasp of the full machine learning workflow-from data collection and model training to deployment, inference, optimization, and evaluation.
We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.
Required Skills & Experience • 3-5 years in ML/AI engineering roles owning training and/or serving in production at scale. • Demonstrated success delivering high-throughput, low-latency ML services with reliability and cost improvements. • Experience collaborating across Research, Platform/Infra, Data, and Product functions. • Bachelors in computer science, Electrical/Computer Engineering, or a related field required; Master's preferred (or equivalent industry experience). • Strong systems/ML engineering with exposure to distributed training and inference optimization.
Benefit packages for this role will start on the 31st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.
In this role you'll need: Deep Learning Frameworks: Hands-on experience with PyTorch (main focus) and familiarity with TensorFlow.
Large-Scale Model Training: Exposure to advanced training techniques like Distributed Data Parallel (DDP), Fully Sharded Data Parallel (FSDP), ZeRO, and model parallelism (pipeline/tensor). Experience with distributed training is a strong plus.
Model Optimization: Skilled in improving model performance through techniques like quantization (PTQ, QAT, AWQ, GPTQ), pruning, knowledge distillation, KV-cache tuning, and using efficient attention mechanisms like Flash Attention.
Scalable Model Serving: Understanding of how to deploy models at scale, including autoscaling, load balancing, streaming, batching, and caching. Comfortable working alongside platform engineers to build robust serving pipelines.
Data & Storage Systems: Proficient with both SQL and NoSQL databases, vector databases (e.g., FAISS, Milvus, Pinecone, pgvector), and data formats like Parquet and Delta. Familiar with object storage systems.
Code Quality: Writes efficient, clean, and maintainable code with a focus on performance.
End-to-End ML Lifecycle: Solid grasp of the full machine learning workflow-from data collection and model training to deployment, inference, optimization, and evaluation.
We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.
Required Skills & Experience • 3-5 years in ML/AI engineering roles owning training and/or serving in production at scale. • Demonstrated success delivering high-throughput, low-latency ML services with reliability and cost improvements. • Experience collaborating across Research, Platform/Infra, Data, and Product functions. • Bachelors in computer science, Electrical/Computer Engineering, or a related field required; Master's preferred (or equivalent industry experience). • Strong systems/ML engineering with exposure to distributed training and inference optimization.
Benefit packages for this role will start on the 31st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.