About this opportunity
Talentify lists this Senior AI/ML Engineer opportunity in workfromhome, Georgia. Review the employer’s description below for duties, qualifications and application requirements.
Job description
Our Client, an IT Services and Consultant company, is looking for a Senior AI/ML Engineer for their Atlanta, GA/Remote location.
Responsibilities
Design and implement supervised, unsupervised, and reinforcement learning models tailored to complex business problems.
Conduct exploratory data analysis, feature engineering, and statistical modelling on large-scale datasets.
Evaluate model performance using appropriate metrics and validation techniques; iterate to improve accuracy and robustness.
Build and maintain end-to-end ML pipelines from data ingestion to model serving and monitoring in production.
Collaborate with data engineers, software engineers, and business stakeholders to translate requirements into ML solutions.
Research, prototype, and integrate state-of-the-art algorithms and frameworks to solve novel problems.
Document models, experiments, and design decisions to ensure reproducibility and knowledge sharing.
Stay current with advances in ML research and assess applicability to the organization’s use cases.
Requirements
Bachelor's or master’s degree in computer science, Statistics, Mathematics, or a related quantitative field (Ph.D. is a plus).
5-9 years of hands-on experience in machine learning and data science roles.
Strong mathematical foundation - linear algebra, calculus, probability, and statistics.
Demonstrated ability to take ML projects from research to production.
Experience working with structured and unstructured data at scale.
Required Technical Expertise
Supervised Learning
Linear regression and logistic regression,
Decision trees, Random Forest, Gradient Boosting (XGBoost, LightGBM, CatBoost),
Support Vector Machines (SVMs) and kernel methods,
Neural networks - CNNs, RNNs, LSTMs, and Transformers,
Classification, regression, and ranking problems,
Cross-validation, bias-variance trade-off, regularization (L1/L2, dropout)
Unsupervised Learning
Clustering: K-Means, DBSCAN, Gaussian Mixture Models, hierarchical clustering
Dimensionality reduction: PCA, t-SNE, UMAP
Autoencoders and variational autoencoders (VAEs)
Anomaly detection and outlier identification
Association rule mining (Apriori, FP-Growth)
Topic modelling (LDA, NMF)
Reinforcement Learning
Markov Decision Processes (MDPs) states, actions, rewards, transitions
Model-free methods: Q-Learning, SARSA, Deep Q-Networks (DQN)
Policy gradient methods: REINFORCE, PPO, A3C / A2C
Actor-Critic architectures
Multi-armed bandits and contextual bandits
Reward shaping, environment design, and simulation frameworks (OpenAI Gym)
Why Should You Apply?
Health Benefits
Referral Program
Excellent growth and advancement opportunities
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Worksite address
workfromhome, GA, 30383, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.