📍 Location: India / Remote (WFH) 🕒 Schedule: Mon–Fri, 10 AM–6 PM 📅 Type: Full-Time 💼 Experience: 3–5 Years About the Role We’re hiring a Senior AI/ML Engineer to lead the design, development, and deployment of scalable AI solutions—including Generative AI, LLMs, and sustainability-driven ML systems . This is a high-impact, hands-on role where you’ll collaborate cross-functionally, own the end-to-end ML lifecycle, and build products that deliver real-world business value across industries like FinTech, HealthTech, and more. Company Description SynerPeak HR Consultants specializes in connecting exceptional talent with forward-thinking companies. They help organizations scale by delivering top-tier professionals who align with their culture, values, and goals. With expertise in various industries, SynerPeak offers end-to-end recruitment solutions, executive search, talent mapping, employer branding consultation, and contract-based hiring. What You'll Bring Strong command of Python, SQL , and ML frameworks: scikit-learn, TensorFlow, PyTorch Experience with ML pipelines (Airflow, MLflow, Kubeflow) and cloud platforms (AWS/GCP/Azure) Skilled in model deployment , MLOps , containerization (Docker, Kubernetes), CI/CD Familiar with deep learning , LLMs , RAG , and Agentic AI frameworks (LangChain, OpenAI API) Key Responsibilities ML & GenAI Engineering Build and deploy models for NLP, recommendation, classification, etc. Fine-tune LLMs and implement RAG-based multi-agent GenAI systems Manage full ML lifecycle: deployment, monitoring, optimisation, drift detection Handle data preprocessing, feature engineering, and model evaluation Work with cross-functional teams and contribute to product decisions Convert business goals into AI-driven technical solutions Stay ahead in AI/ML research and rapidly apply new techniques You’re a Great Fit If You... Take initiative and own your decisions Know when not to use GenAI Can clearly explain trade-offs to engineers & business stakeholders Why Join Us? Flexibility & Time Off Flexible hours Paid leave (sick, personal, bereavement) Fully paid insurance 6 months maternity & 3 months paternity leave Extras Team events (virtual + in-person) Equity options & competitive salary What You'll Work On 50% : Building robust, production-grade AI systems 25% : Prototyping and researching innovative ML/GenAI ideas 25% : Collaborating with stakeholders to solve real-world business challenges Ready to lead real-world AI innovation? Apply now and be part of something transformative. Please send your updated Resume and cover letter to hr@synerpeak.com
💻 What You’ll Do: Machine Learning & AI Development Model Development: Train and optimize ML models for carbon sequestration monitoring, geospatial analytics, and predictive weathering rates. Deep Learning: Apply CNNs, transformers, and diffusion models for remote sensing and climate forecasting. Geospatial AI: Build ML-powered GIS tools, land-use change models, and soil mineralization estimations. Data Engineering & MLOps Scalable ML Pipelines: Develop large-scale data pipelines for climate, soil, and geospatial datasets using Airflow, Dask, or Spark. Cloud & Infrastructure: Deploy ML models on AWS, GCP, or Azure using Docker, Kubernetes, and CI/CD workflows. Big Data Processing: Work with satellite, drone, and sensor data for real-time carbon tracking. Geospatial & Climate Data Analysis Remote Sensing: Process data from Sentinel, Landsat, MODIS, LiDAR, integrating with Google Earth Engine (GEE) and QGIS. Geochemistry & Soil Science: Model mineral weathering, CO2 drawdown, and climate resilience impacts. Time-Series & Climate Data: Analyze NOAA, ERA5, CMIP6 datasets for climate pattern detection. 👀 What We’re Looking For: Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or a related field. 3+ years of experience in machine learning, deep learning, or AI development. Python (NumPy, Pandas, PyTorch, TensorFlow, Scikit-learn) Cloud ML & MLOps (AWS, GCP, Azure, Kubernetes, Docker, CI/CD) Geospatial & Remote Sensing (GIS, Google Earth Engine, QGIS, Sentinel/Landsat) Big Data & Pipelines (Airflow, Dask, Spark, ETL, SQL, NoSQL) Deep Learning & Computer Vision (CNNs, Transformers, Self-Supervised Learning) Familiarity with geospatial data, climate modeling, or environmental science is a plus. Strong problem-solving skills and the ability to work in a collaborative team environment. 🔖 Preferred Qualifications: Experience in climate tech, sustainability, or carbon markets. Contributions to open-source ML or environmental science projects. Background in graph neural networks, diffusion models, or self-supervised learning.