MACHINE LEARNING ENGINEER

Machine Learning Engineer - From startups to Fortune 500s, we help companies make sense of their business challenges by applying modern data analytics techniques, visualizations, and AI / ML. Founded by engineers, we love passionate technologists and data analysts. Our startup DNA means everyone on the team makes a direct contribution to the growth of the company. Position Overview : Blue Orange seeks an experienced Machine Learning Engineer to expand our dynamic multi-disciplinary team. The ideal candidate will possess a deep passion for machine learning, AI technologies, and innovative data solutions. With proficiency in advanced machine learning techniques, strong skills in programming languages such as Python, deep expertise around data analytics and feature engineering, solid experience working with some of the main ML and D frameworks (Sklearn, XGBoost, LightGBM, TensorFlow, and / or PyTorch), experience working with containerized technologies (Docker), and a proven track record of building cloud-native solutions with at least 1 of the main clouds (AWS, GCP, and / or Azure), MLOps and LLMs. The candidate will play a crucial role in driving our machine-learning initiatives forward. The candidate will have excellent communication skills to collaborate with technical and non-technical stakeholders effectively. At Blue Orange, you'll have the opportunity to work on cutting-edge projects, leveraging modern machine-learning and AI techniques to deliver tangible business outcomes and drive innovation in our data-driven solutions. Responsibilities : Develop and Implement Machine Learning and AI Models : Design, build, and deploy advanced machine learning models. Improve model performance by conducting feature engineering, hyperparameter search, and metric selection. Optional: Experience working with classical NLP: Intent recognition, Named Entity Recognition (NER), and Part of Speech Tagging (POS) using Sklearn, Spacy, and Hugging Face. Build LLM-based products and stay up to date with current developments. Proficiency using Hugging Face, OpenAI, Anthropic, and / or Cohere tools. Design and build custom APIs with tools like FastAPI. Build LLM orchestration systems with tools like LangChain, LLamaIndex, Semantic Kernel, and / or HayStack. Build predictive analytics and modeling products using tools like Sklearn, Sktime, XGboosts, and / or LightGBM. Data Analytics and Processing : Analyze large, complex datasets to extract actionable insights and inform model development. Implement data preprocessing, cleansing, and quality checks to ensure data quality. Cloud-Native Solutions and MLOps : Develop and maintain cloud-native machine learning solutions using any of the major clouds: AWS (Lambda, EMR, GLUE, ECS, EKS), GCP (GKE, Anthos, Cloud Run), and / or Azure (CA, KS). Implement and manage MLOps practices to automate and streamline the ML model deployment process using tools such as MLflow and / or Weights and Biases. Containerization Technologies : Utilize containerization technologies like Docker and Docker-compose to ensure consistent and scalable deployment of machine learning models using FastAPI microservices. Quality Assurance and Best Practices : Ensure the highest quality of machine learning models through rigorous testing and validation using unit and integration testing with CI / CD pipelines through GitHub actions. Advocate and adhere to best software (i. e. , SOLID, DRY, Git version control, etc. ) and machine learning practices (train, val, test data splits, baseline definition, overfitting management, etc. ) within the team. Requirements : 1 - 3 years experience practicing ML / AI data engineering. Degree in Computer Science, Engineering, Mathematics, or a related field. Strong mathematical skills, particularly in statistics and linear algebra. Experience with NLP and LLM-based technologies and frameworks. Proficiency in programming languages such as Python. Experience with cloud-based technologies AWS, GCP, and / or Azure. Expertise in training and deploying ML / AI-powered solutions in cloud environments. Preferred Qualifications : Advanced degree in a relevant field. Publications in relevant AI / ML communities and journals. Deep Learning Expertise in Tensorflow and / or Pytorch. Experience Fine-tuning OpenSource LLMs and deploying them. Great Expectations and / or DBT is a plus. Benefits : Fully remote. Flexible Schedule. Unlimited Paid Time Off (PTO). Paid parental / bereavement leave. Worldwide recognized clients to build skills for an excellent resume. Top-notch team to learn and grow with. Monthly Salary Range: USD $4,541. 67 $5,000 (annual: USD $54,500 $60,000). Blue Orange Digital is an equal-opportunity employer. Background checks may be required for certain positions / projects. #J-18808-Ljbffr