Method, Inc.
About Method
Method is a global design and engineering consultancy founded in 1999. We craft practical, powerful digital experiences that improve lives and transform businesses. Our teams are based in New York, Charlotte, Atlanta, London, Poland, Bengaluru, and remote locations, working with a wide range of organizations in many industries. Role Overview
We’re seeking a hands‑on ML Engineer to join our Data & AI team. You will design, develop, and optimise machine learning models and LLMs to drive intelligent automation and decision‑making across the platform, working closely with MLOps and data engineering teams. Responsibilities
Design, build, and deploy scalable machine learning solutions across a range of use cases. Collaborate with MLOps Engineers, Data Engineers, and AI Architects to develop robust, production‑ready ML pipelines. Lead experimentation and model development, selecting appropriate algorithms and evaluation metrics. Participate in feature engineering, data preprocessing, and dataset curation with a focus on reproducibility and version control. Work within an ecosystem that leverages tools such as JupyterHub, MLflow, Kubernetes, and custom workflows. Drive continuous improvements to the model lifecycle through automation, testing, and feedback‑driven iteration. Qualifications
5+ years of professional experience in data science and ML engineering with a focus on end‑to‑end solutions. Strong proficiency in Python (Pandas, NumPy, scikit‑learn, PyTorch, TensorFlow, Plotly, Seaborn, Flask/Django/FastAPI). Experience designing models that integrate smoothly into ML pipelines or workflow orchestration. Solid understanding of contemporary machine learning techniques and best practices. Experience with MLflow or similar experimentation & tracking tools. Proven ability to optimise model inference for speed and cost‑effectiveness. Ability to prepare and export models for on‑prem inference, including packaging models and tokenizers. Experience with LLM development, prompt engineering, and serving LLMs on‑prem. Familiarity with RAG architecture. Benefits
Continuing education opportunities Flexible PTO and work‑from‑home policies Private medical care (extendable to family) Cafeteria system as part of the benefit platform Group life insurance Creative tax‑deductible cost savings Next Steps
If Method sounds like the place for you, please submit an application and include any relevant portfolio, GitHub, or other public workspace links. Equal Employment Opportunity
As set forth in Method, a GlobalLogic company’s Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.
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Method is a global design and engineering consultancy founded in 1999. We craft practical, powerful digital experiences that improve lives and transform businesses. Our teams are based in New York, Charlotte, Atlanta, London, Poland, Bengaluru, and remote locations, working with a wide range of organizations in many industries. Role Overview
We’re seeking a hands‑on ML Engineer to join our Data & AI team. You will design, develop, and optimise machine learning models and LLMs to drive intelligent automation and decision‑making across the platform, working closely with MLOps and data engineering teams. Responsibilities
Design, build, and deploy scalable machine learning solutions across a range of use cases. Collaborate with MLOps Engineers, Data Engineers, and AI Architects to develop robust, production‑ready ML pipelines. Lead experimentation and model development, selecting appropriate algorithms and evaluation metrics. Participate in feature engineering, data preprocessing, and dataset curation with a focus on reproducibility and version control. Work within an ecosystem that leverages tools such as JupyterHub, MLflow, Kubernetes, and custom workflows. Drive continuous improvements to the model lifecycle through automation, testing, and feedback‑driven iteration. Qualifications
5+ years of professional experience in data science and ML engineering with a focus on end‑to‑end solutions. Strong proficiency in Python (Pandas, NumPy, scikit‑learn, PyTorch, TensorFlow, Plotly, Seaborn, Flask/Django/FastAPI). Experience designing models that integrate smoothly into ML pipelines or workflow orchestration. Solid understanding of contemporary machine learning techniques and best practices. Experience with MLflow or similar experimentation & tracking tools. Proven ability to optimise model inference for speed and cost‑effectiveness. Ability to prepare and export models for on‑prem inference, including packaging models and tokenizers. Experience with LLM development, prompt engineering, and serving LLMs on‑prem. Familiarity with RAG architecture. Benefits
Continuing education opportunities Flexible PTO and work‑from‑home policies Private medical care (extendable to family) Cafeteria system as part of the benefit platform Group life insurance Creative tax‑deductible cost savings Next Steps
If Method sounds like the place for you, please submit an application and include any relevant portfolio, GitHub, or other public workspace links. Equal Employment Opportunity
As set forth in Method, a GlobalLogic company’s Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.
#J-18808-Ljbffr