Technical Manager - MI/ML

Purpose of Job

To lead a data science and AI/ML team that analyzes large-scale aquaculture and IoT data, designs statistically rigorous experiments, develops and evaluates machine learning and deep learning models, and translates model outputs into practical decisions that improve aquaculture productivity and operational efficiency. The role will sustain and continuously improve Eruvaka’s core automatic feeding algorithms, while working with cross-functional teams to enable health and farm intelligence capabilities through data science, modelling, validation, and decision-support methods.

Responsibilities

Understand business goals and real-world problems in Eruvaka IoT solutions for aquaculture and  solve the same using data.

Lead and guide a team of data scientists and ML engineers, and plan the growth of team members.

Organize large data sets and build a scalable approach for data analysis.

Apply robust statistical analysis, causal reasoning, and machine learning techniques to develop, validate, and evaluate models with clear assumptions, confidence intervals, error analysis, and business impact measures.

Establish metrics and methods to measure and improve performance of Eruvaka solutions (models, algorithms, products).

Design experiments, A/B tests, observational analyses, and field trials with appropriate control groups, sampling methods, success criteria, statistical power, and bias-mitigation practices.

Support health and farm intelligence initiatives by working with cross-functional teams to build and evaluate prediction, anomaly detection, early warning, and decision-support models using sensor, feeding, environmental, and field-observation data.

Define field trial evaluation frameworks, track pre- and post-deployment performance, and partner with domain experts to convert trial results into product and algorithm improvements.

Work closely with product, cloud, firmware, customer success, field, and domain teams to understand needs, align priorities, and translate business problems into data science work.

Own and drive the maintenance and development of Eruvaka feeding algorithms, from requirements to field trials.

Partner with cross-functional teams to convert roadmap needs into data science experiments, pilots, validation methods, and scalable algorithms.

Be the point of contact for various stakeholders, including customers, management, and internal teams.

Lead projects from ideation to production.

Qualification, Experience and Required Skills

Bachelor’s or higher degree in Computer Science, Statistics, Electrical Engineering, Electronics

Engineering, Physics, Mathematics, or related fields.

Must have delivered at least two production-grade projects.

Must have strong hands-on experience with programming languages like Python, PySpark and  SQL, and frameworks such as NumPy, Pandas, Scikit-learn, etc.

Should have experience developing and deploying machine learning and deep learning solutions.

Expertise in classification, regression, time series, decision trees, optimization, etc.

Engage in  MLOps and model development workflows. Experience working with cloud platforms such as AWS, Azure, or GCP.

Competence in software development methodologies, code versioning tools such as GitLab, and project tracking tools such as Jira.

Define best practices, standards, and templates for AI solutions.

Excellent communication and client/stakeholder management skills

Preferred experience in agriculture, aquaculture, animal health, biotechnology, IoT, or other sensor-driven domains where models are validated through real-world field data.

Good to have

Experience with big data tools and familiarity with visualization tools.

Experience in the area of IoT Experience deploying models at the edge.