**Company: Sagri Job Description Summary: Sagri is a social impact startup using satellite data and AI to address global food crises and climate change challenges. They offer services like Actaba, Detaba, and Sagri. Ideal candidates are passionate, fast learners who can make a societal impact. The services aim to support sustainable agriculture, reduce carbon emissions, and improve farmers’ profitability. The company is looking for a Machine Learning Engineer or Data Scientist with leadership experience and skills in Machine learning, statistics, Python programming, cloud providers, and software engineering. The candidate should resonate with Sagri’s vision, value team communication, be motivated to learn new skills, and enjoy working in a fast-paced environment. Job Description: Join Sagri, a pioneering social impact startup utilizing satellite data and AI technology to address global food crisis and climate change challenges. Be part of a dynamic team using satellite data and AI technology to address global food crises and climate change. You’ll be able to develop unique services like Actaba, Detaba, and Sagri, each offering distinct, innovative solutions in agricultural management and optimization. Embrace a role where job titles do not limit your technical skills and creativity but are harnessed to tackle diverse, impactful challenges. Ideal candidates are passionate, fast learners ready to make a significant societal impact and thrive in a collaborative, fast-paced startup environment. With your software engineering expertise, join us to drive meaningful change and shape a sustainable future. We provide three primary services. Actaba: this service focuses on surveying the use of agricultural land. It’s already deployed in over 40 municipalities and aims… to expand further, evolving based on customer feedback. Actaba stands out as it has no direct competitors and has received positive evaluations from its users. Detaba: this is an app for surveying crop planting. Utilizing satellite imagery, Detaba infers the crops planted in a given area. This aids municipalities in ensuring lands are used as declared, simplifying the process of granting subsidies and gathering statistical data. Sagri: an app tailored for farming operations. It assists in optimizing fertilizer use by analyzing soil components through satellite imagery. Minimizing excess fertilizer use reduces workload and addresses environmental concerns like global warming. Sagri is currently under joint development with WAGRI, aiming to enhance agricultural data integration and provision. These services aim to support sustainable agriculture, reduce carbon emissions, and improve farmers’ profitability by leveraging carbon credits, particularly in emerging countries. Who You Are • 5+ years of work experience as a Machine Learning Engineer or Data Scientist with at least two years in a leadership role. • Experience tech leading cross-team engineering efforts. • Experience with Machine learning and statistics at scale, with an ability to apply these skills to new domains such as satellite-based remote sensing. • Strong software engineering practices and a background in Python programming, debugging/profiling, version control, and system design. • Hands-on experience with at least one cloud provider, such as GCP, AWS, or Azure. • Comfort with fast-paced execution and rapid iteration startup environment. Excited by the product impact. • Passion for environmental sustainability and a desire to make a meaningful impact on the planet. What You’ll Do • Conduct research, develop, and implement machine learning systems for recommendation systems. • Identify the most effective algorithms and refine models to achieve peak performance. • Assess and analyze the efficacy of models, recommending enhancements as needed. • Integrate machine learning models into production. • Continuously update knowledge on cutting-edge machine learning technologies and practices. • Lead and manage crucial stages of the machine learning project lifecycle. Who we want to work with: • Resonate with Sagri’s vision, mission, and values • Have the desire to solve societal issues through software engineering • Value team communication and information sharing, highly motivated to learn and acquire new skills • Keen on listening to customer feedback and responding earnestly • Enjoy working in a fast-paced environment, embracing significant changes. Here are some things we value but don’t expect all: • Have worked with or experienced in satellite-based remote sensing, and have some understanding of agriculture
Company:Sagri
Qualifications:
Language requirements:
Specific requirements:
Educational level:
Level of experience (years):Senior (5+ years of experience)
“Fine-tuning” means adapting an existing machine learning model for specific tasks or use cases. In this post I’m going to walk you through how you can fine tune a large language model for sentence similarity using some hand annotated test data. This example is in the psychology domain. You need training data consisting of pairs of sentences, and a “ground truth” of how similar you want those sentences to be when you train your custom sentence similarity model.
Hire an NLP developer and untangle the power of natural language in your projects The world is buzzing with the possibilities of natural language processing (NLP). From chatbots that understand your needs to algorithms that analyse mountains of text data, NLP is revolutionising industries across the board. But harnessing this power requires the right expertise. That’s where finding the perfect NLP developer comes in. Post a job in NLP on naturallanguageprocessing.
Natural language processing What is natural language processing? Natural language processing, or NLP, is a field of artificial intelligence that focuses on the interaction between computers and humans using natural language. NLP is a branch of AI but is really a mixture of disciplines such as linguistics, computer science, and engineering. There are a number of approaches to NLP, ranging from rule-based modelling of human language to statistical methods. Common uses of NLP include speech recognition systems, the voice assistants available on smartphones, and chatbots.
